{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority Differentials.APPENDIX I RESULTS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 7 Aug 2024, 22:24:44
{txt}
{com}. 
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. ***** SUPPLEMENTARY APPENDIX STATISTICAL ANALYSES:  APPENDIX I: CONSIDERING SPILLOVER OR CONTAGION EFFECTS ACROSS SOCIAL IDENTITY 'OUT-GROUPS' /// ******
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. *** ACCESS DATABASE FOR THE PROJECT: FEVS DATA FROM 2010-2019 AND 'MATCHED' OPM DATA: POST-ESTIMATION OF MANUSCRIPT RESULTS ****
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. use "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\2010-2019_DATA FINAL.08-07-2024.post-estimation.dta", replace 
{txt}
{com}. 
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. **************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
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. *** MODEL I1: Women SGPD contagion for Minority/Non-Minority Respondents as an Added Set of Covariates ***
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. regress lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.gender   ln_ratio_fem_tot_men_tot   minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio i.agencyid i.year c.ln_ratio_fmsup_fmsub##i.minority, vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_fmsup_fmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.minority} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(18, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0404
                                                {txt}Root MSE          =    {res} .51453

{txt}{ralign 97:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 32}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 33}{c |}{col 45}    Robust
{col 1}            lndiversity2zeroadj{col 33}{c |} Coefficient{col 45}  std. err.{col 57}      t{col 65}   P>|t|{col 73}     [95% con{col 86}f. interval]
{hline 32}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}ln_ratio_fmsup_fmsub {c |}{col 33}{res}{space 2} .1465575{col 45}{space 2} .0413712{col 56}{space 1}    3.54{col 65}{space 3}0.001{col 73}{space 4} .0645169{col 86}{space 3}  .228598
{txt}{space 23}1.gender {c |}{col 33}{res}{space 2}-.0403111{col 45}{space 2} .0064574{col 56}{space 1}   -6.24{col 65}{space 3}0.000{col 73}{space 4}-.0531164{col 86}{space 3}-.0275058
{txt}{space 31} {c |}
{space 2}gender#c.ln_ratio_fmsup_fmsub {c |}
{space 29}1  {c |}{col 33}{res}{space 2}-.0021315{col 45}{space 2} .0193726{col 56}{space 1}   -0.11{col 65}{space 3}0.913{col 73}{space 4}-.0405482{col 86}{space 3} .0362851
{txt}{space 31} {c |}
{space 7}ln_ratio_fem_tot_men_tot {c |}{col 33}{res}{space 2}-.0055239{col 45}{space 2} .0554514{col 56}{space 1}   -0.10{col 65}{space 3}0.921{col 73}{space 4}-.1154861{col 86}{space 3} .1044383
{txt}{space 23}minority {c |}{col 33}{res}{space 2}-.0871994{col 45}{space 2} .0069696{col 56}{space 1}  -12.51{col 65}{space 3}0.000{col 73}{space 4}-.1010204{col 86}{space 3}-.0733783
{txt}{space 21}supervisor {c |}{col 33}{res}{space 2} .1271003{col 45}{space 2} .0074323{col 56}{space 1}   17.10{col 65}{space 3}0.000{col 73}{space 4} .1123618{col 86}{space 3} .1418389
{txt}{space 17}topoffgender_2 {c |}{col 33}{res}{space 2}-.0028334{col 45}{space 2} .0044911{col 56}{space 1}   -0.63{col 65}{space 3}0.529{col 73}{space 4}-.0117394{col 86}{space 3} .0060726
{txt}{space 11}lntotworkforce_count {c |}{col 33}{res}{space 2} .0752357{col 45}{space 2} .0323369{col 56}{space 1}    2.33{col 65}{space 3}0.022{col 73}{space 4} .0111104{col 86}{space 3}  .139361
{txt}{space 3}ln_professionals_total_ratio {c |}{col 33}{res}{space 2} .0079056{col 45}{space 2} .0415729{col 56}{space 1}    0.19{col 65}{space 3}0.850{col 73}{space 4} -.074535{col 86}{space 3} .0903463
{txt}{space 31} {c |}
{space 23}agencyid {c |}
{space 29}2  {c |}{col 33}{res}{space 2} .3058881{col 45}{space 2} .1143805{col 56}{space 1}    2.67{col 65}{space 3}0.009{col 73}{space 4} .0790672{col 86}{space 3}  .532709
{txt}{space 29}3  {c |}{col 33}{res}{space 2} .0903164{col 45}{space 2} .0540189{col 56}{space 1}    1.67{col 65}{space 3}0.098{col 73}{space 4}-.0168051{col 86}{space 3}  .197438
{txt}{space 29}4  {c |}{col 33}{res}{space 2} .4301657{col 45}{space 2} .1506734{col 56}{space 1}    2.85{col 65}{space 3}0.005{col 73}{space 4} .1313748{col 86}{space 3} .7289566
{txt}{space 29}5  {c |}{col 33}{res}{space 2} .2624841{col 45}{space 2}  .104386{col 56}{space 1}    2.51{col 65}{space 3}0.013{col 73}{space 4} .0554828{col 86}{space 3} .4694854
{txt}{space 29}6  {c |}{col 33}{res}{space 2} .2487991{col 45}{space 2} .1104473{col 56}{space 1}    2.25{col 65}{space 3}0.026{col 73}{space 4} .0297779{col 86}{space 3} .4678202
{txt}{space 29}7  {c |}{col 33}{res}{space 2} .3553185{col 45}{space 2} .1823869{col 56}{space 1}    1.95{col 65}{space 3}0.054{col 73}{space 4}-.0063616{col 86}{space 3} .7169986
{txt}{space 29}8  {c |}{col 33}{res}{space 2} .3010811{col 45}{space 2} .1423895{col 56}{space 1}    2.11{col 65}{space 3}0.037{col 73}{space 4} .0187174{col 86}{space 3} .5834447
{txt}{space 29}9  {c |}{col 33}{res}{space 2}-.0119237{col 45}{space 2} .0226341{col 56}{space 1}   -0.53{col 65}{space 3}0.599{col 73}{space 4}-.0568079{col 86}{space 3} .0329605
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{txt}{space 28}82  {c |}{col 33}{res}{space 2} .3533538{col 45}{space 2} .1842631{col 56}{space 1}    1.92{col 65}{space 3}0.058{col 73}{space 4}-.0120468{col 86}{space 3} .7187544
{txt}{space 28}83  {c |}{col 33}{res}{space 2} .4290082{col 45}{space 2} .1452113{col 56}{space 1}    2.95{col 65}{space 3}0.004{col 73}{space 4} .1410487{col 86}{space 3} .7169677
{txt}{space 28}84  {c |}{col 33}{res}{space 2} .3309984{col 45}{space 2} .1844048{col 56}{space 1}    1.79{col 65}{space 3}0.076{col 73}{space 4}-.0346832{col 86}{space 3}   .69668
{txt}{space 28}85  {c |}{col 33}{res}{space 2} .4061725{col 45}{space 2} .1470975{col 56}{space 1}    2.76{col 65}{space 3}0.007{col 73}{space 4} .1144727{col 86}{space 3} .6978722
{txt}{space 28}86  {c |}{col 33}{res}{space 2} .4620401{col 45}{space 2} .1895486{col 56}{space 1}    2.44{col 65}{space 3}0.016{col 73}{space 4} .0861582{col 86}{space 3}  .837922
{txt}{space 28}87  {c |}{col 33}{res}{space 2} .4650473{col 45}{space 2} .1908287{col 56}{space 1}    2.44{col 65}{space 3}0.017{col 73}{space 4}  .086627{col 86}{space 3} .8434677
{txt}{space 28}88  {c |}{col 33}{res}{space 2} .2545526{col 45}{space 2} .1349667{col 56}{space 1}    1.89{col 65}{space 3}0.062{col 73}{space 4}-.0130914{col 86}{space 3} .5221966
{txt}{space 28}89  {c |}{col 33}{res}{space 2}  .298366{col 45}{space 2}   .14574{col 56}{space 1}    2.05{col 65}{space 3}0.043{col 73}{space 4} .0093581{col 86}{space 3}  .587374
{txt}{space 28}90  {c |}{col 33}{res}{space 2} .0785124{col 45}{space 2} .1087514{col 56}{space 1}    0.72{col 65}{space 3}0.472{col 73}{space 4}-.1371456{col 86}{space 3} .2941705
{txt}{space 28}91  {c |}{col 33}{res}{space 2} .1950809{col 45}{space 2} .1092138{col 56}{space 1}    1.79{col 65}{space 3}0.077{col 73}{space 4}-.0214941{col 86}{space 3} .4116559
{txt}{space 28}92  {c |}{col 33}{res}{space 2} .0806132{col 45}{space 2} .0445916{col 56}{space 1}    1.81{col 65}{space 3}0.074{col 73}{space 4}-.0078135{col 86}{space 3}   .16904
{txt}{space 28}93  {c |}{col 33}{res}{space 2}  .428204{col 45}{space 2} .1462331{col 56}{space 1}    2.93{col 65}{space 3}0.004{col 73}{space 4} .1382182{col 86}{space 3} .7181898
{txt}{space 28}94  {c |}{col 33}{res}{space 2}  .461663{col 45}{space 2} .1663925{col 56}{space 1}    2.77{col 65}{space 3}0.007{col 73}{space 4} .1317004{col 86}{space 3} .7916256
{txt}{space 28}95  {c |}{col 33}{res}{space 2} .2174562{col 45}{space 2} .1442635{col 56}{space 1}    1.51{col 65}{space 3}0.135{col 73}{space 4}-.0686237{col 86}{space 3} .5035361
{txt}{space 28}96  {c |}{col 33}{res}{space 2} .3405024{col 45}{space 2} .1541284{col 56}{space 1}    2.21{col 65}{space 3}0.029{col 73}{space 4}   .03486{col 86}{space 3} .6461448
{txt}{space 28}97  {c |}{col 33}{res}{space 2} .3969201{col 45}{space 2} .1482122{col 56}{space 1}    2.68{col 65}{space 3}0.009{col 73}{space 4} .1030098{col 86}{space 3} .6908303
{txt}{space 28}98  {c |}{col 33}{res}{space 2} .5580382{col 45}{space 2} .1838427{col 56}{space 1}    3.04{col 65}{space 3}0.003{col 73}{space 4} .1934712{col 86}{space 3} .9226051
{txt}{space 28}99  {c |}{col 33}{res}{space 2} .0900871{col 45}{space 2} .0915578{col 56}{space 1}    0.98{col 65}{space 3}0.327{col 73}{space 4}-.0914754{col 86}{space 3} .2716495
{txt}{space 27}100  {c |}{col 33}{res}{space 2} .2522537{col 45}{space 2} .1481206{col 56}{space 1}    1.70{col 65}{space 3}0.092{col 73}{space 4} -.041475{col 86}{space 3} .5459823
{txt}{space 27}101  {c |}{col 33}{res}{space 2} .4052765{col 45}{space 2}  .134015{col 56}{space 1}    3.02{col 65}{space 3}0.003{col 73}{space 4} .1395197{col 86}{space 3} .6710333
{txt}{space 27}102  {c |}{col 33}{res}{space 2}  .255366{col 45}{space 2}  .153194{col 56}{space 1}    1.67{col 65}{space 3}0.099{col 73}{space 4}-.0484234{col 86}{space 3} .5591554
{txt}{space 27}103  {c |}{col 33}{res}{space 2} .0737065{col 45}{space 2} .1049819{col 56}{space 1}    0.70{col 65}{space 3}0.484{col 73}{space 4}-.1344765{col 86}{space 3} .2818895
{txt}{space 27}104  {c |}{col 33}{res}{space 2}-.1000519{col 45}{space 2} .0748677{col 56}{space 1}   -1.34{col 65}{space 3}0.184{col 73}{space 4}-.2485174{col 86}{space 3} .0484135
{txt}{space 27}105  {c |}{col 33}{res}{space 2} .3351945{col 45}{space 2}  .152503{col 56}{space 1}    2.20{col 65}{space 3}0.030{col 73}{space 4} .0327753{col 86}{space 3} .6376137
{txt}{space 31} {c |}
{space 27}year {c |}
{space 26}2011  {c |}{col 33}{res}{space 2}-.0040947{col 45}{space 2} .0032349{col 56}{space 1}   -1.27{col 65}{space 3}0.208{col 73}{space 4}-.0105095{col 86}{space 3} .0023202
{txt}{space 26}2012  {c |}{col 33}{res}{space 2} .0001705{col 45}{space 2}  .004499{col 56}{space 1}    0.04{col 65}{space 3}0.970{col 73}{space 4}-.0087512{col 86}{space 3} .0090923
{txt}{space 26}2013  {c |}{col 33}{res}{space 2}-.0009862{col 45}{space 2} .0049837{col 56}{space 1}   -0.20{col 65}{space 3}0.844{col 73}{space 4}-.0108691{col 86}{space 3} .0088968
{txt}{space 26}2014  {c |}{col 33}{res}{space 2}-.0069789{col 45}{space 2} .0070344{col 56}{space 1}   -0.99{col 65}{space 3}0.323{col 73}{space 4}-.0209284{col 86}{space 3} .0069707
{txt}{space 26}2015  {c |}{col 33}{res}{space 2}  -.01456{col 45}{space 2} .0085898{col 56}{space 1}   -1.70{col 65}{space 3}0.093{col 73}{space 4}-.0315939{col 86}{space 3}  .002474
{txt}{space 26}2016  {c |}{col 33}{res}{space 2}-.0177762{col 45}{space 2} .0074108{col 56}{space 1}   -2.40{col 65}{space 3}0.018{col 73}{space 4} -.032472{col 86}{space 3}-.0030803
{txt}{space 26}2017  {c |}{col 33}{res}{space 2}-.0036381{col 45}{space 2} .0095706{col 56}{space 1}   -0.38{col 65}{space 3}0.705{col 73}{space 4} -.022617{col 86}{space 3} .0153407
{txt}{space 26}2018  {c |}{col 33}{res}{space 2}-.0327434{col 45}{space 2} .0073566{col 56}{space 1}   -4.45{col 65}{space 3}0.000{col 73}{space 4}-.0473318{col 86}{space 3}-.0181549
{txt}{space 26}2019  {c |}{col 33}{res}{space 2}-.0710337{col 45}{space 2} .0084326{col 56}{space 1}   -8.42{col 65}{space 3}0.000{col 73}{space 4}-.0877558{col 86}{space 3}-.0543117
{txt}{space 31} {c |}
{space 11}ln_ratio_fmsup_fmsub {c |}{col 33}{res}{space 2}        0{col 45}{txt}  (omitted)
{space 21}1.minority {c |}{col 33}{res}{space 2}        0{col 45}{txt}  (omitted)
{space 31} {c |}
minority#c.ln_ratio_fmsup_fmsub {c |}
{space 29}1  {c |}{col 33}{res}{space 2} .0210193{col 45}{space 2} .0171648{col 56}{space 1}    1.22{col 65}{space 3}0.224{col 73}{space 4}-.0130192{col 86}{space 3} .0550578
{txt}{space 31} {c |}
{space 26}_cons {c |}{col 33}{res}{space 2}-.1262591{col 45}{space 2} .4148925{col 56}{space 1}   -0.30{col 65}{space 3}0.761{col 73}{space 4}-.9490065{col 86}{space 3} .6964884
{txt}{hline 32}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891373{col 50}    19{col 58}  3782784{col 69}  3783026
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1465575{col 26}{space 2} .0413712{col 37}{space 1}    3.54{col 46}{space 3}0.001{col 54}{space 4} .0645169{col 67}{space 3}  .228598
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0021315{col 26}{space 2} .0193726{col 37}{space 1}   -0.11{col 46}{space 3}0.913{col 54}{space 4}-.0405482{col 67}{space 3} .0362851
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. *
. *
. *
. *
. 
. *** MODEL I2: Minority SGPD contagion for Women/Men Respondents as an Added Set of Covariates  ***
. 
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. regress  lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority   ln_ratio_min_tot_nmin_tot  gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year c.ln_ratio_mnmsup_mnmsub##i.gender, vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_mnmsup_mnmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.gender} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(18, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0403
                                                {txt}Root MSE          =    {res} .51455

{txt}{ralign 99:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 34}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 35}{c |}{col 47}    Robust
{col 1}              lndiversity2zeroadj{col 35}{c |} Coefficient{col 47}  std. err.{col 59}      t{col 67}   P>|t|{col 75}     [95% con{col 88}f. interval]
{hline 34}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}ln_ratio_mnmsup_mnmsub {c |}{col 35}{res}{space 2} .0465808{col 47}{space 2} .0332234{col 58}{space 1}    1.40{col 67}{space 3}0.164{col 75}{space 4}-.0193023{col 88}{space 3}  .112464
{txt}{space 23}1.minority {c |}{col 35}{res}{space 2}-.0785304{col 47}{space 2} .0057332{col 58}{space 1}  -13.70{col 67}{space 3}0.000{col 75}{space 4}-.0898995{col 88}{space 3}-.0671614
{txt}{space 33} {c |}
minority#c.ln_ratio_mnmsup_mnmsub {c |}
{space 31}1  {c |}{col 35}{res}{space 2}  .046197{col 47}{space 2} .0160056{col 58}{space 1}    2.89{col 67}{space 3}0.005{col 75}{space 4} .0144573{col 88}{space 3} .0779366
{txt}{space 33} {c |}
{space 8}ln_ratio_min_tot_nmin_tot {c |}{col 35}{res}{space 2} .0535668{col 47}{space 2} .0449687{col 58}{space 1}    1.19{col 67}{space 3}0.236{col 75}{space 4}-.0356079{col 88}{space 3} .1427414
{txt}{space 27}gender {c |}{col 35}{res}{space 2}-.0353446{col 47}{space 2} .0062837{col 58}{space 1}   -5.62{col 67}{space 3}0.000{col 75}{space 4}-.0478055{col 88}{space 3}-.0228837
{txt}{space 23}supervisor {c |}{col 35}{res}{space 2} .1271846{col 47}{space 2} .0074075{col 58}{space 1}   17.17{col 67}{space 3}0.000{col 75}{space 4} .1124953{col 88}{space 3}  .141874
{txt}{space 17}topoffminority_2 {c |}{col 35}{res}{space 2} .0075333{col 47}{space 2} .0059208{col 58}{space 1}    1.27{col 67}{space 3}0.206{col 75}{space 4}-.0042079{col 88}{space 3} .0192744
{txt}{space 13}lntotworkforce_count {c |}{col 35}{res}{space 2} .0652442{col 47}{space 2} .0401859{col 58}{space 1}    1.62{col 67}{space 3}0.107{col 75}{space 4} -.014446{col 88}{space 3} .1449343
{txt}{space 5}ln_professionals_total_ratio {c |}{col 35}{res}{space 2} .0218624{col 47}{space 2} .0502974{col 58}{space 1}    0.43{col 67}{space 3}0.665{col 75}{space 4}-.0778792{col 88}{space 3}  .121604
{txt}{space 33} {c |}
{space 25}agencyid {c |}
{space 31}2  {c |}{col 35}{res}{space 2} .2131559{col 47}{space 2} .1222689{col 58}{space 1}    1.74{col 67}{space 3}0.084{col 75}{space 4}-.0293079{col 88}{space 3} .4556196
{txt}{space 31}3  {c |}{col 35}{res}{space 2} .0348022{col 47}{space 2} .0540345{col 58}{space 1}    0.64{col 67}{space 3}0.521{col 75}{space 4}-.0723502{col 88}{space 3} .1419546
{txt}{space 31}4  {c |}{col 35}{res}{space 2} .2844296{col 47}{space 2}  .163898{col 58}{space 1}    1.74{col 67}{space 3}0.086{col 75}{space 4}-.0405864{col 88}{space 3} .6094455
{txt}{space 31}5  {c |}{col 35}{res}{space 2} .1689808{col 47}{space 2} .1271328{col 58}{space 1}    1.33{col 67}{space 3}0.187{col 75}{space 4}-.0831282{col 88}{space 3} .4210898
{txt}{space 31}6  {c |}{col 35}{res}{space 2} .1759757{col 47}{space 2} .1182991{col 58}{space 1}    1.49{col 67}{space 3}0.140{col 75}{space 4}-.0586159{col 88}{space 3} .4105673
{txt}{space 31}7  {c |}{col 35}{res}{space 2} .2461241{col 47}{space 2} .2169055{col 58}{space 1}    1.13{col 67}{space 3}0.259{col 75}{space 4}-.1840075{col 88}{space 3} .6762558
{txt}{space 31}8  {c |}{col 35}{res}{space 2} .2343312{col 47}{space 2} .1623113{col 58}{space 1}    1.44{col 67}{space 3}0.152{col 75}{space 4}-.0875382{col 88}{space 3} .5562005
{txt}{space 31}9  {c |}{col 35}{res}{space 2} -.055502{col 47}{space 2} .0229518{col 58}{space 1}   -2.42{col 67}{space 3}0.017{col 75}{space 4}-.1010163{col 88}{space 3}-.0099877
{txt}{space 30}10  {c |}{col 35}{res}{space 2} .1924585{col 47}{space 2} .2309132{col 58}{space 1}    0.83{col 67}{space 3}0.406{col 75}{space 4} -.265451{col 88}{space 3}  .650368
{txt}{space 30}11  {c |}{col 35}{res}{space 2} .1613913{col 47}{space 2} .1046414{col 58}{space 1}    1.54{col 67}{space 3}0.126{col 75}{space 4}-.0461166{col 88}{space 3} .3688992
{txt}{space 30}12  {c |}{col 35}{res}{space 2} .3178071{col 47}{space 2} .2144348{col 58}{space 1}    1.48{col 67}{space 3}0.141{col 75}{space 4}-.1074251{col 88}{space 3} .7430393
{txt}{space 30}13  {c |}{col 35}{res}{space 2}   .31443{col 47}{space 2} .1624312{col 58}{space 1}    1.94{col 67}{space 3}0.056{col 75}{space 4}-.0076772{col 88}{space 3} .6365371
{txt}{space 30}14  {c |}{col 35}{res}{space 2}  .157804{col 47}{space 2} .1099399{col 58}{space 1}    1.44{col 67}{space 3}0.154{col 75}{space 4} -.060211{col 88}{space 3} .3758191
{txt}{space 30}15  {c |}{col 35}{res}{space 2} .2349981{col 47}{space 2} .1542285{col 58}{space 1}    1.52{col 67}{space 3}0.131{col 75}{space 4}-.0708428{col 88}{space 3} .5408389
{txt}{space 30}16  {c |}{col 35}{res}{space 2}  .204269{col 47}{space 2} .2875117{col 58}{space 1}    0.71{col 67}{space 3}0.479{col 75}{space 4}-.3658776{col 88}{space 3} .7744155
{txt}{space 30}17  {c |}{col 35}{res}{space 2} .0465626{col 47}{space 2} .1877735{col 58}{space 1}    0.25{col 67}{space 3}0.805{col 75}{space 4}-.3257993{col 88}{space 3} .4189244
{txt}{space 30}18  {c |}{col 35}{res}{space 2}  .310039{col 47}{space 2} .1691335{col 58}{space 1}    1.83{col 67}{space 3}0.070{col 75}{space 4}-.0253591{col 88}{space 3} .6454371
{txt}{space 30}19  {c |}{col 35}{res}{space 2} .1803697{col 47}{space 2}  .114347{col 58}{space 1}    1.58{col 67}{space 3}0.118{col 75}{space 4}-.0463847{col 88}{space 3} .4071241
{txt}{space 30}20  {c |}{col 35}{res}{space 2} .0602755{col 47}{space 2} .1202089{col 58}{space 1}    0.50{col 67}{space 3}0.617{col 75}{space 4}-.1781032{col 88}{space 3} .2986542
{txt}{space 30}21  {c |}{col 35}{res}{space 2} .2126773{col 47}{space 2} .1095467{col 58}{space 1}    1.94{col 67}{space 3}0.055{col 75}{space 4} -.004558{col 88}{space 3} .4299125
{txt}{space 30}22  {c |}{col 35}{res}{space 2} .1490919{col 47}{space 2} .1735416{col 58}{space 1}    0.86{col 67}{space 3}0.392{col 75}{space 4}-.1950475{col 88}{space 3} .4932313
{txt}{space 30}23  {c |}{col 35}{res}{space 2}-.1026059{col 47}{space 2} .0874257{col 58}{space 1}   -1.17{col 67}{space 3}0.243{col 75}{space 4}-.2759743{col 88}{space 3} .0707626
{txt}{space 30}24  {c |}{col 35}{res}{space 2} .2485229{col 47}{space 2} .1221095{col 58}{space 1}    2.04{col 67}{space 3}0.044{col 75}{space 4} .0063751{col 88}{space 3} .4906707
{txt}{space 30}25  {c |}{col 35}{res}{space 2} .1902858{col 47}{space 2} .1485885{col 58}{space 1}    1.28{col 67}{space 3}0.203{col 75}{space 4}-.1043707{col 88}{space 3} .4849423
{txt}{space 30}26  {c |}{col 35}{res}{space 2} .0525904{col 47}{space 2} .1314661{col 58}{space 1}    0.40{col 67}{space 3}0.690{col 75}{space 4}-.2081118{col 88}{space 3} .3132926
{txt}{space 30}27  {c |}{col 35}{res}{space 2} .3587625{col 47}{space 2} .1967859{col 58}{space 1}    1.82{col 67}{space 3}0.071{col 75}{space 4}-.0314714{col 88}{space 3} .7489963
{txt}{space 30}28  {c |}{col 35}{res}{space 2}-.0483618{col 47}{space 2} .1113606{col 58}{space 1}   -0.43{col 67}{space 3}0.665{col 75}{space 4}-.2691941{col 88}{space 3} .1724706
{txt}{space 30}29  {c |}{col 35}{res}{space 2} .0812786{col 47}{space 2} .1873192{col 58}{space 1}    0.43{col 67}{space 3}0.665{col 75}{space 4}-.2901823{col 88}{space 3} .4527395
{txt}{space 30}30  {c |}{col 35}{res}{space 2} .1617744{col 47}{space 2} .1732942{col 58}{space 1}    0.93{col 67}{space 3}0.353{col 75}{space 4}-.1818746{col 88}{space 3} .5054234
{txt}{space 30}31  {c |}{col 35}{res}{space 2}-.0191508{col 47}{space 2} .1792586{col 58}{space 1}   -0.11{col 67}{space 3}0.915{col 75}{space 4}-.3746274{col 88}{space 3} .3363257
{txt}{space 30}32  {c |}{col 35}{res}{space 2} .2072208{col 47}{space 2} .1421691{col 58}{space 1}    1.46{col 67}{space 3}0.148{col 75}{space 4}-.0747059{col 88}{space 3} .4891476
{txt}{space 30}33  {c |}{col 35}{res}{space 2} .1206181{col 47}{space 2} .0894245{col 58}{space 1}    1.35{col 67}{space 3}0.180{col 75}{space 4} -.056714{col 88}{space 3} .2979502
{txt}{space 30}34  {c |}{col 35}{res}{space 2}-.1464786{col 47}{space 2} .2269144{col 58}{space 1}   -0.65{col 67}{space 3}0.520{col 75}{space 4}-.5964584{col 88}{space 3} .3035012
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{txt}{space 30}36  {c |}{col 35}{res}{space 2} .2140474{col 47}{space 2} .1348977{col 58}{space 1}    1.59{col 67}{space 3}0.116{col 75}{space 4}-.0534598{col 88}{space 3} .4815546
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{txt}{space 33} {c |}
{space 29}year {c |}
{space 28}2011  {c |}{col 35}{res}{space 2}-.0023395{col 47}{space 2} .0037603{col 58}{space 1}   -0.62{col 67}{space 3}0.535{col 75}{space 4}-.0097964{col 88}{space 3} .0051174
{txt}{space 28}2012  {c |}{col 35}{res}{space 2} .0046991{col 47}{space 2} .0045009{col 58}{space 1}    1.04{col 67}{space 3}0.299{col 75}{space 4}-.0042263{col 88}{space 3} .0136245
{txt}{space 28}2013  {c |}{col 35}{res}{space 2} .0027309{col 47}{space 2}  .005595{col 58}{space 1}    0.49{col 67}{space 3}0.627{col 75}{space 4}-.0083642{col 88}{space 3} .0138259
{txt}{space 28}2014  {c |}{col 35}{res}{space 2}-.0023103{col 47}{space 2}  .006578{col 58}{space 1}   -0.35{col 67}{space 3}0.726{col 75}{space 4}-.0153547{col 88}{space 3} .0107341
{txt}{space 28}2015  {c |}{col 35}{res}{space 2} -.010168{col 47}{space 2} .0079999{col 58}{space 1}   -1.27{col 67}{space 3}0.207{col 75}{space 4} -.026032{col 88}{space 3}  .005696
{txt}{space 28}2016  {c |}{col 35}{res}{space 2}-.0130932{col 47}{space 2} .0079745{col 58}{space 1}   -1.64{col 67}{space 3}0.104{col 75}{space 4}-.0289068{col 88}{space 3} .0027205
{txt}{space 28}2017  {c |}{col 35}{res}{space 2}-.0028909{col 47}{space 2} .0117803{col 58}{space 1}   -0.25{col 67}{space 3}0.807{col 75}{space 4}-.0262517{col 88}{space 3} .0204699
{txt}{space 28}2018  {c |}{col 35}{res}{space 2}-.0292462{col 47}{space 2} .0107071{col 58}{space 1}   -2.73{col 67}{space 3}0.007{col 75}{space 4}-.0504788{col 88}{space 3}-.0080136
{txt}{space 28}2019  {c |}{col 35}{res}{space 2}-.0684237{col 47}{space 2}  .012098{col 58}{space 1}   -5.66{col 67}{space 3}0.000{col 75}{space 4}-.0924144{col 88}{space 3}-.0444329
{txt}{space 33} {c |}
{space 11}ln_ratio_mnmsup_mnmsub {c |}{col 35}{res}{space 2}        0{col 47}{txt}  (omitted)
{space 25}1.gender {c |}{col 35}{res}{space 2}        0{col 47}{txt}  (omitted)
{space 33} {c |}
{space 2}gender#c.ln_ratio_mnmsup_mnmsub {c |}
{space 31}1  {c |}{col 35}{res}{space 2} .0121416{col 47}{space 2} .0109783{col 58}{space 1}    1.11{col 67}{space 3}0.271{col 75}{space 4}-.0096288{col 88}{space 3} .0339119
{txt}{space 33} {c |}
{space 28}_cons {c |}{col 35}{res}{space 2} .0383267{col 47}{space 2} .5059178{col 58}{space 1}    0.08{col 67}{space 3}0.940{col 75}{space 4}-.9649273{col 88}{space 3} 1.041581
{txt}{hline 34}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891476{col 50}    19{col 58}  3782989{col 69}  3783231
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0465808{col 26}{space 2} .0332234{col 37}{space 1}    1.40{col 46}{space 3}0.164{col 54}{space 4}-.0193023{col 67}{space 3}  .112464
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .046197{col 26}{space 2} .0160056{col 37}{space 1}    2.89{col 46}{space 3}0.005{col 54}{space 4} .0144573{col 67}{space 3} .0779366
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. 
. *** MODEL I3: HETEROGENEOUS Women SGPD contagion for HETEROGENEOUS Minority/Non-Minority RESPONDENTS as an Added Set of Covariates  ***
. 
. regress lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.women_het   ln_ratio_fem_tot_men_tot  minority  supervisor  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year  c.ln_ratio_fmsup_fmsub##i.minority_het, vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_fmsup_fmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.minority_het} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.minority_het} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.minority_het#c.ln_ratio_fmsup_fmsub} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0407
                                                {txt}Root MSE          =    {res} .51445

{txt}{ralign 101:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 36}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 37}{c |}{col 49}    Robust
{col 1}                lndiversity2zeroadj{col 37}{c |} Coefficient{col 49}  std. err.{col 61}      t{col 69}   P>|t|{col 77}     [95% con{col 90}f. interval]
{hline 36}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
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{txt}{space 32}90  {c |}{col 37}{res}{space 2}  .078339{col 49}{space 2}  .108853{col 60}{space 1}    0.72{col 69}{space 3}0.473{col 77}{space 4}-.1375205{col 90}{space 3} .2941986
{txt}{space 32}91  {c |}{col 37}{res}{space 2} .1942562{col 49}{space 2} .1091687{col 60}{space 1}    1.78{col 69}{space 3}0.078{col 77}{space 4}-.0222295{col 90}{space 3} .4107418
{txt}{space 32}92  {c |}{col 37}{res}{space 2} .0801174{col 49}{space 2} .0446301{col 60}{space 1}    1.80{col 69}{space 3}0.076{col 77}{space 4}-.0083857{col 90}{space 3} .1686206
{txt}{space 32}93  {c |}{col 37}{res}{space 2} .4275676{col 49}{space 2} .1461975{col 60}{space 1}    2.92{col 69}{space 3}0.004{col 77}{space 4} .1376524{col 90}{space 3} .7174827
{txt}{space 32}94  {c |}{col 37}{res}{space 2} .4627469{col 49}{space 2}  .166401{col 60}{space 1}    2.78{col 69}{space 3}0.006{col 77}{space 4} .1327675{col 90}{space 3} .7927262
{txt}{space 32}95  {c |}{col 37}{res}{space 2} .2155449{col 49}{space 2} .1442688{col 60}{space 1}    1.49{col 69}{space 3}0.138{col 77}{space 4}-.0705456{col 90}{space 3} .5016354
{txt}{space 32}96  {c |}{col 37}{res}{space 2} .3396422{col 49}{space 2} .1540543{col 60}{space 1}    2.20{col 69}{space 3}0.030{col 77}{space 4} .0341467{col 90}{space 3} .6451377
{txt}{space 32}97  {c |}{col 37}{res}{space 2} .3946164{col 49}{space 2} .1481557{col 60}{space 1}    2.66{col 69}{space 3}0.009{col 77}{space 4}  .100818{col 90}{space 3} .6884148
{txt}{space 32}98  {c |}{col 37}{res}{space 2} .5575851{col 49}{space 2} .1837318{col 60}{space 1}    3.03{col 69}{space 3}0.003{col 77}{space 4}  .193238{col 90}{space 3} .9219322
{txt}{space 32}99  {c |}{col 37}{res}{space 2} .0897696{col 49}{space 2} .0916224{col 60}{space 1}    0.98{col 69}{space 3}0.329{col 77}{space 4}-.0919212{col 90}{space 3} .2714603
{txt}{space 31}100  {c |}{col 37}{res}{space 2} .2507607{col 49}{space 2} .1481135{col 60}{space 1}    1.69{col 69}{space 3}0.093{col 77}{space 4} -.042954{col 90}{space 3} .5444753
{txt}{space 31}101  {c |}{col 37}{res}{space 2} .4039964{col 49}{space 2} .1339804{col 60}{space 1}    3.02{col 69}{space 3}0.003{col 77}{space 4} .1383083{col 90}{space 3} .6696846
{txt}{space 31}102  {c |}{col 37}{res}{space 2}  .253851{col 49}{space 2} .1532905{col 60}{space 1}    1.66{col 69}{space 3}0.101{col 77}{space 4}-.0501299{col 90}{space 3} .5578318
{txt}{space 31}103  {c |}{col 37}{res}{space 2}  .072002{col 49}{space 2}  .105052{col 60}{space 1}    0.69{col 69}{space 3}0.495{col 77}{space 4}-.1363202{col 90}{space 3} .2803241
{txt}{space 31}104  {c |}{col 37}{res}{space 2}-.1010579{col 49}{space 2} .0749191{col 60}{space 1}   -1.35{col 69}{space 3}0.180{col 77}{space 4}-.2496252{col 90}{space 3} .0475095
{txt}{space 31}105  {c |}{col 37}{res}{space 2}  .334526{col 49}{space 2} .1524202{col 60}{space 1}    2.19{col 69}{space 3}0.030{col 77}{space 4} .0322711{col 90}{space 3}  .636781
{txt}{space 35} {c |}
{space 31}year {c |}
{space 30}2011  {c |}{col 37}{res}{space 2} -.004137{col 49}{space 2}  .003236{col 60}{space 1}   -1.28{col 69}{space 3}0.204{col 77}{space 4}-.0105541{col 90}{space 3} .0022802
{txt}{space 30}2012  {c |}{col 37}{res}{space 2} .0000318{col 49}{space 2} .0044885{col 60}{space 1}    0.01{col 69}{space 3}0.994{col 77}{space 4} -.008869{col 90}{space 3} .0089326
{txt}{space 30}2013  {c |}{col 37}{res}{space 2} -.001068{col 49}{space 2} .0049846{col 60}{space 1}   -0.21{col 69}{space 3}0.831{col 77}{space 4}-.0109526{col 90}{space 3} .0088167
{txt}{space 30}2014  {c |}{col 37}{res}{space 2}-.0070837{col 49}{space 2} .0070343{col 60}{space 1}   -1.01{col 69}{space 3}0.316{col 77}{space 4} -.021033{col 90}{space 3} .0068656
{txt}{space 30}2015  {c |}{col 37}{res}{space 2}-.0146602{col 49}{space 2}  .008585{col 60}{space 1}   -1.71{col 69}{space 3}0.091{col 77}{space 4}-.0316845{col 90}{space 3} .0023641
{txt}{space 30}2016  {c |}{col 37}{res}{space 2}-.0179475{col 49}{space 2} .0074177{col 60}{space 1}   -2.42{col 69}{space 3}0.017{col 77}{space 4}-.0326572{col 90}{space 3}-.0032379
{txt}{space 30}2017  {c |}{col 37}{res}{space 2}-.0037047{col 49}{space 2}  .009597{col 60}{space 1}   -0.39{col 69}{space 3}0.700{col 77}{space 4}-.0227359{col 90}{space 3} .0153265
{txt}{space 30}2018  {c |}{col 37}{res}{space 2}-.0328583{col 49}{space 2} .0073644{col 60}{space 1}   -4.46{col 69}{space 3}0.000{col 77}{space 4}-.0474621{col 90}{space 3}-.0182545
{txt}{space 30}2019  {c |}{col 37}{res}{space 2}-.0711175{col 49}{space 2} .0084385{col 60}{space 1}   -8.43{col 69}{space 3}0.000{col 77}{space 4}-.0878513{col 90}{space 3}-.0543838
{txt}{space 35} {c |}
{space 15}ln_ratio_fmsup_fmsub {c |}{col 37}{res}{space 2}        0{col 49}{txt}  (omitted)
{space 35} {c |}
{space 23}minority_het {c |}
{space 33}1  {c |}{col 37}{res}{space 2}        0{col 49}{txt}  (omitted)
{space 33}2  {c |}{col 37}{res}{space 2}        0{col 49}{txt}  (omitted)
{space 35} {c |}
minority_het#c.ln_ratio_fmsup_fmsub {c |}
{space 33}1  {c |}{col 37}{res}{space 2} .0245127{col 49}{space 2} .0167777{col 60}{space 1}    1.46{col 69}{space 3}0.147{col 77}{space 4}-.0087581{col 90}{space 3} .0577835
{txt}{space 33}2  {c |}{col 37}{res}{space 2}        0{col 49}{txt}  (omitted)
{space 35} {c |}
{space 30}_cons {c |}{col 37}{res}{space 2}-.1295156{col 49}{space 2} .4150222{col 60}{space 1}   -0.31{col 69}{space 3}0.756{col 77}{space 4}-.9525202{col 90}{space 3}  .693489
{txt}{hline 36}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891016{col 50}    21{col 58}  3782073{col 69}  3782341
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1445813{col 26}{space 2} .0414248{col 37}{space 1}    3.49{col 46}{space 3}0.001{col 54}{space 4} .0624344{col 67}{space 3} .2267283
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .003801{col 26}{space 2} .0218678{col 37}{space 1}    0.17{col 46}{space 3}0.862{col 54}{space 4}-.0395636{col 67}{space 3} .0471656
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .019931{col 26}{space 2} .0249086{col 37}{space 1}    0.80{col 46}{space 3}0.425{col 54}{space 4}-.0294638{col 67}{space 3} .0693257
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub -  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0161299{col 26}{space 2} .0183733{col 37}{space 1}    0.88{col 46}{space 3}0.382{col 54}{space 4}-.0203051{col 67}{space 3} .0525649
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. 
. *** MODEL I4: HETEROGENEOUS Minority SGPD contagion for Minority/Non-Minority Respondents for HETEROGENEOUS Minority/Non-Minority RESPONDENTS as an Added Set of Covariates  ***
. 
. regress lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority_het   ln_ratio_min_tot_nmin_tot   gender supervisor  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year  c.ln_ratio_mnmsup_mnmsub##i.women_het, vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_mnmsup_mnmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.women_het} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.women_het} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.women_het#c.ln_ratio_mnmsup_mnmsub} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(20, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0406
                                                {txt}Root MSE          =    {res} .51448

{txt}{ralign 103:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 38}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 39}{c |}{col 51}    Robust
{col 1}                  lndiversity2zeroadj{col 39}{c |} Coefficient{col 51}  std. err.{col 63}      t{col 71}   P>|t|{col 79}     [95% con{col 92}f. interval]
{hline 38}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}ln_ratio_mnmsup_mnmsub {c |}{col 39}{res}{space 2} .0509926{col 51}{space 2} .0334716{col 62}{space 1}    1.52{col 71}{space 3}0.131{col 79}{space 4}-.0153828{col 92}{space 3} .1173681
{txt}{space 37} {c |}
{space 25}minority_het {c |}
{space 35}1  {c |}{col 39}{res}{space 2}-.0668919{col 51}{space 2} .0064589{col 62}{space 1}  -10.36{col 71}{space 3}0.000{col 79}{space 4}-.0797001{col 92}{space 3}-.0540837
{txt}{space 35}2  {c |}{col 39}{res}{space 2}-.0955452{col 51}{space 2} .0067369{col 62}{space 1}  -14.18{col 71}{space 3}0.000{col 79}{space 4}-.1089048{col 92}{space 3}-.0821857
{txt}{space 37} {c |}
minority_het#c.ln_ratio_mnmsup_mnmsub {c |}
{space 35}1  {c |}{col 39}{res}{space 2} .0295631{col 51}{space 2} .0174441{col 62}{space 1}    1.69{col 71}{space 3}0.093{col 79}{space 4}-.0050292{col 92}{space 3} .0641554
{txt}{space 35}2  {c |}{col 39}{res}{space 2} .0570874{col 51}{space 2} .0220802{col 62}{space 1}    2.59{col 71}{space 3}0.011{col 79}{space 4} .0133015{col 92}{space 3} .1008732
{txt}{space 37} {c |}
{space 12}ln_ratio_min_tot_nmin_tot {c |}{col 39}{res}{space 2} .0535055{col 51}{space 2} .0449963{col 62}{space 1}    1.19{col 71}{space 3}0.237{col 79}{space 4}-.0357238{col 92}{space 3} .1427348
{txt}{space 31}gender {c |}{col 39}{res}{space 2} -.024989{col 51}{space 2} .0075451{col 62}{space 1}   -3.31{col 71}{space 3}0.001{col 79}{space 4}-.0399513{col 92}{space 3}-.0100267
{txt}{space 27}supervisor {c |}{col 39}{res}{space 2} .1273935{col 51}{space 2} .0074108{col 62}{space 1}   17.19{col 71}{space 3}0.000{col 79}{space 4} .1126977{col 92}{space 3} .1420894
{txt}{space 21}topoffminority_2 {c |}{col 39}{res}{space 2} .0075279{col 51}{space 2} .0059297{col 62}{space 1}    1.27{col 71}{space 3}0.207{col 79}{space 4}-.0042308{col 92}{space 3} .0192867
{txt}{space 17}lntotworkforce_count {c |}{col 39}{res}{space 2} .0649605{col 51}{space 2} .0402234{col 62}{space 1}    1.61{col 71}{space 3}0.109{col 79}{space 4}-.0148041{col 92}{space 3}  .144725
{txt}{space 9}ln_professionals_total_ratio {c |}{col 39}{res}{space 2} .0217619{col 51}{space 2} .0503199{col 62}{space 1}    0.43{col 71}{space 3}0.666{col 79}{space 4}-.0780243{col 92}{space 3} .1215481
{txt}{space 37} {c |}
{space 29}agencyid {c |}
{space 35}2  {c |}{col 39}{res}{space 2}  .211624{col 51}{space 2} .1224119{col 62}{space 1}    1.73{col 71}{space 3}0.087{col 79}{space 4}-.0311235{col 92}{space 3} .4543714
{txt}{space 35}3  {c |}{col 39}{res}{space 2} .0331618{col 51}{space 2} .0540989{col 62}{space 1}    0.61{col 71}{space 3}0.541{col 79}{space 4}-.0741183{col 92}{space 3} .1404418
{txt}{space 35}4  {c |}{col 39}{res}{space 2} .2819456{col 51}{space 2} .1640365{col 62}{space 1}    1.72{col 71}{space 3}0.089{col 79}{space 4}-.0433449{col 92}{space 3} .6072361
{txt}{space 35}5  {c |}{col 39}{res}{space 2} .1681692{col 51}{space 2}  .127233{col 62}{space 1}    1.32{col 71}{space 3}0.189{col 79}{space 4}-.0841386{col 92}{space 3}  .420477
{txt}{space 35}6  {c |}{col 39}{res}{space 2} .1744086{col 51}{space 2}   .11852{col 62}{space 1}    1.47{col 71}{space 3}0.144{col 79}{space 4}-.0606211{col 92}{space 3} .4094382
{txt}{space 35}7  {c |}{col 39}{res}{space 2} .2459238{col 51}{space 2} .2170134{col 62}{space 1}    1.13{col 71}{space 3}0.260{col 79}{space 4}-.1844219{col 92}{space 3} .6762696
{txt}{space 35}8  {c |}{col 39}{res}{space 2} .2329324{col 51}{space 2} .1624396{col 62}{space 1}    1.43{col 71}{space 3}0.155{col 79}{space 4}-.0891914{col 92}{space 3} .5550562
{txt}{space 35}9  {c |}{col 39}{res}{space 2}-.0557719{col 51}{space 2} .0229579{col 62}{space 1}   -2.43{col 71}{space 3}0.017{col 79}{space 4}-.1012983{col 92}{space 3}-.0102455
{txt}{space 34}10  {c |}{col 39}{res}{space 2} .1896596{col 51}{space 2} .2310868{col 62}{space 1}    0.82{col 71}{space 3}0.414{col 79}{space 4}-.2685942{col 92}{space 3} .6479134
{txt}{space 34}11  {c |}{col 39}{res}{space 2} .1600078{col 51}{space 2} .1047165{col 62}{space 1}    1.53{col 71}{space 3}0.130{col 79}{space 4}-.0476489{col 92}{space 3} .3676646
{txt}{space 34}12  {c |}{col 39}{res}{space 2} .3165547{col 51}{space 2} .2145914{col 62}{space 1}    1.48{col 71}{space 3}0.143{col 79}{space 4}-.1089881{col 92}{space 3} .7420975
{txt}{space 34}13  {c |}{col 39}{res}{space 2} .3140016{col 51}{space 2} .1625644{col 62}{space 1}    1.93{col 71}{space 3}0.056{col 79}{space 4}-.0083698{col 92}{space 3}  .636373
{txt}{space 34}14  {c |}{col 39}{res}{space 2} .1572896{col 51}{space 2} .1100618{col 62}{space 1}    1.43{col 71}{space 3}0.156{col 79}{space 4}-.0609671{col 92}{space 3} .3755463
{txt}{space 34}15  {c |}{col 39}{res}{space 2} .2329192{col 51}{space 2} .1542455{col 62}{space 1}    1.51{col 71}{space 3}0.134{col 79}{space 4}-.0729555{col 92}{space 3} .5387938
{txt}{space 34}16  {c |}{col 39}{res}{space 2} .2060766{col 51}{space 2} .2875292{col 62}{space 1}    0.72{col 71}{space 3}0.475{col 79}{space 4}-.3641047{col 92}{space 3} .7762579
{txt}{space 34}17  {c |}{col 39}{res}{space 2} .0451943{col 51}{space 2} .1878959{col 62}{space 1}    0.24{col 71}{space 3}0.810{col 79}{space 4}-.3274104{col 92}{space 3}  .417799
{txt}{space 34}18  {c |}{col 39}{res}{space 2}  .308638{col 51}{space 2} .1692658{col 62}{space 1}    1.82{col 71}{space 3}0.071{col 79}{space 4}-.0270225{col 92}{space 3} .6442985
{txt}{space 34}19  {c |}{col 39}{res}{space 2} .1794027{col 51}{space 2} .1144413{col 62}{space 1}    1.57{col 71}{space 3}0.120{col 79}{space 4}-.0475388{col 92}{space 3} .4063441
{txt}{space 34}20  {c |}{col 39}{res}{space 2}  .058995{col 51}{space 2} .1202045{col 62}{space 1}    0.49{col 71}{space 3}0.625{col 79}{space 4} -.179375{col 92}{space 3}  .297365
{txt}{space 34}21  {c |}{col 39}{res}{space 2}  .210868{col 51}{space 2} .1096696{col 62}{space 1}    1.92{col 71}{space 3}0.057{col 79}{space 4} -.006611{col 92}{space 3}  .428347
{txt}{space 34}22  {c |}{col 39}{res}{space 2}  .147961{col 51}{space 2} .1736342{col 62}{space 1}    0.85{col 71}{space 3}0.396{col 79}{space 4}-.1963621{col 92}{space 3} .4922841
{txt}{space 34}23  {c |}{col 39}{res}{space 2}-.1043913{col 51}{space 2} .0876054{col 62}{space 1}   -1.19{col 71}{space 3}0.236{col 79}{space 4} -.278116{col 92}{space 3} .0693334
{txt}{space 34}24  {c |}{col 39}{res}{space 2} .2481214{col 51}{space 2} .1222084{col 62}{space 1}    2.03{col 71}{space 3}0.045{col 79}{space 4} .0057776{col 92}{space 3} .4904652
{txt}{space 34}25  {c |}{col 39}{res}{space 2} .1888882{col 51}{space 2} .1486882{col 62}{space 1}    1.27{col 71}{space 3}0.207{col 79}{space 4}-.1059661{col 92}{space 3} .4837425
{txt}{space 34}26  {c |}{col 39}{res}{space 2} .0512829{col 51}{space 2} .1315692{col 62}{space 1}    0.39{col 71}{space 3}0.697{col 79}{space 4}-.2096238{col 92}{space 3} .3121895
{txt}{space 34}27  {c |}{col 39}{res}{space 2} .3577533{col 51}{space 2} .1969626{col 62}{space 1}    1.82{col 71}{space 3}0.072{col 79}{space 4} -.032831{col 92}{space 3} .7483375
{txt}{space 34}28  {c |}{col 39}{res}{space 2}-.0500183{col 51}{space 2} .1114744{col 62}{space 1}   -0.45{col 71}{space 3}0.655{col 79}{space 4}-.2710763{col 92}{space 3} .1710396
{txt}{space 34}29  {c |}{col 39}{res}{space 2} .0795926{col 51}{space 2} .1874655{col 62}{space 1}    0.42{col 71}{space 3}0.672{col 79}{space 4}-.2921585{col 92}{space 3} .4513437
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{txt}{space 37} {c |}
{space 33}year {c |}
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{txt}{space 37} {c |}
{space 15}ln_ratio_mnmsup_mnmsub {c |}{col 39}{res}{space 2}        0{col 51}{txt}  (omitted)
{space 37} {c |}
{space 28}women_het {c |}
{space 35}1  {c |}{col 39}{res}{space 2}        0{col 51}{txt}  (omitted)
{space 35}2  {c |}{col 39}{res}{space 2}        0{col 51}{txt}  (omitted)
{space 37} {c |}
{space 3}women_het#c.ln_ratio_mnmsup_mnmsub {c |}
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{txt}{space 35}2  {c |}{col 39}{res}{space 2}        0{col 51}{txt}  (omitted)
{space 37} {c |}
{space 32}_cons {c |}{col 39}{res}{space 2} .0383067{col 51}{space 2} .5064066{col 62}{space 1}    0.08{col 71}{space 3}0.940{col 79}{space 4}-.9659166{col 92}{space 3}  1.04253
{txt}{hline 38}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891131{col 50}    21{col 58}  3782304{col 69}  3782572
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. ** BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0509926{col 26}{space 2} .0334716{col 37}{space 1}    1.52{col 46}{space 3}0.131{col 54}{space 4}-.0153828{col 67}{space 3} .1173681
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0295631{col 26}{space 2} .0174441{col 37}{space 1}    1.69{col 46}{space 3}0.093{col 54}{space 4}-.0050292{col 67}{space 3} .0641554
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0570874{col 26}{space 2} .0220802{col 37}{space 1}    2.59{col 46}{space 3}0.011{col 54}{space 4} .0133015{col 67}{space 3} .1008732
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub -  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0275242{col 26}{space 2} .0133062{col 37}{space 1}    2.07{col 46}{space 3}0.041{col 54}{space 4} .0011375{col 67}{space 3}  .053911
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. **************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. *********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. *********** estimating the above models making a more granular distinction between Non-Supervisory and Supervisory Respondents through a triple interaction term ***********
. 
. 
. ********************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. *** MODEL I5: Women Absolute SGPD contagion for Minority/Non-Minority Respondents as an Added Set of Covariates  -- CONTROLLING FOR RACIAL/ETHNIC MINORITY SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.gender##i.supervisor   ln_ratio_fem_tot_men_tot   minority  topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year c.ln_ratio_fmsup_fmsub##i.minority##i.supervisor , vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_fmsup_fmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.minority} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(23, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0405
                                                {txt}Root MSE          =    {res}  .5145

{txt}{ralign 108:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 43}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 44}{c |}{col 56}    Robust
{col 1}                       lndiversity2zeroadj{col 44}{c |} Coefficient{col 56}  std. err.{col 68}      t{col 76}   P>|t|{col 84}     [95% con{col 97}f. interval]
{hline 43}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}ln_ratio_fmsup_fmsub {c |}{col 44}{res}{space 2} .1275063{col 56}{space 2} .0448418{col 67}{space 1}    2.84{col 76}{space 3}0.005{col 84}{space 4} .0385833{col 97}{space 3} .2164292
{txt}{space 34}1.gender {c |}{col 44}{res}{space 2} -.039732{col 56}{space 2} .0098668{col 67}{space 1}   -4.03{col 76}{space 3}0.000{col 84}{space 4}-.0592981{col 97}{space 3}-.0201658
{txt}{space 42} {c |}
{space 13}gender#c.ln_ratio_fmsup_fmsub {c |}
{space 40}1  {c |}{col 44}{res}{space 2} .0048597{col 56}{space 2} .0261583{col 67}{space 1}    0.19{col 76}{space 3}0.853{col 84}{space 4}-.0470132{col 97}{space 3} .0567326
{txt}{space 42} {c |}
{space 30}1.supervisor {c |}{col 44}{res}{space 2} .1460976{col 56}{space 2} .0201381{col 67}{space 1}    7.25{col 76}{space 3}0.000{col 84}{space 4} .1061631{col 97}{space 3} .1860322
{txt}{space 42} {c |}
{space 9}supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 40}1  {c |}{col 44}{res}{space 2} .0663716{col 56}{space 2} .0398642{col 67}{space 1}    1.66{col 76}{space 3}0.099{col 84}{space 4}-.0126806{col 97}{space 3} .1454238
{txt}{space 42} {c |}
{space 25}gender#supervisor {c |}
{space 38}1 1  {c |}{col 44}{res}{space 2}   .00619{col 56}{space 2}  .014562{col 67}{space 1}    0.43{col 76}{space 3}0.672{col 84}{space 4}-.0226871{col 97}{space 3}  .035067
{txt}{space 42} {c |}
{space 2}gender#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 38}1 1  {c |}{col 44}{res}{space 2}-.0028496{col 56}{space 2}  .029848{col 67}{space 1}   -0.10{col 76}{space 3}0.924{col 84}{space 4}-.0620393{col 97}{space 3} .0563401
{txt}{space 42} {c |}
{space 18}ln_ratio_fem_tot_men_tot {c |}{col 44}{res}{space 2}-.0065832{col 56}{space 2} .0554268{col 67}{space 1}   -0.12{col 76}{space 3}0.906{col 84}{space 4}-.1164967{col 97}{space 3} .1033302
{txt}{space 34}minority {c |}{col 44}{res}{space 2}-.0852333{col 56}{space 2}  .007929{col 67}{space 1}  -10.75{col 76}{space 3}0.000{col 84}{space 4}-.1009569{col 97}{space 3}-.0695097
{txt}{space 28}topoffgender_2 {c |}{col 44}{res}{space 2}-.0028048{col 56}{space 2} .0044911{col 67}{space 1}   -0.62{col 76}{space 3}0.534{col 84}{space 4}-.0117107{col 97}{space 3} .0061012
{txt}{space 22}lntotworkforce_count {c |}{col 44}{res}{space 2} .0763571{col 56}{space 2} .0320749{col 67}{space 1}    2.38{col 76}{space 3}0.019{col 84}{space 4} .0127514{col 97}{space 3} .1399628
{txt}{space 14}ln_professionals_total_ratio {c |}{col 44}{res}{space 2} .0072917{col 56}{space 2} .0412578{col 67}{space 1}    0.18{col 76}{space 3}0.860{col 84}{space 4}-.0745242{col 97}{space 3} .0891075
{txt}{space 42} {c |}
{space 34}agencyid {c |}
{space 40}2  {c |}{col 44}{res}{space 2}  .315091{col 56}{space 2} .1133353{col 67}{space 1}    2.78{col 76}{space 3}0.006{col 84}{space 4} .0903429{col 97}{space 3} .5398392
{txt}{space 40}3  {c |}{col 44}{res}{space 2} .0945974{col 56}{space 2} .0535124{col 67}{space 1}    1.77{col 76}{space 3}0.080{col 84}{space 4}-.0115196{col 97}{space 3} .2007145
{txt}{space 40}4  {c |}{col 44}{res}{space 2} .4396335{col 56}{space 2} .1488826{col 67}{space 1}    2.95{col 76}{space 3}0.004{col 84}{space 4} .1443938{col 97}{space 3} .7348733
{txt}{space 40}5  {c |}{col 44}{res}{space 2} .2670913{col 56}{space 2} .1034322{col 67}{space 1}    2.58{col 76}{space 3}0.011{col 84}{space 4} .0619814{col 97}{space 3} .4722012
{txt}{space 40}6  {c |}{col 44}{res}{space 2} .2531475{col 56}{space 2} .1097859{col 67}{space 1}    2.31{col 76}{space 3}0.023{col 84}{space 4} .0354379{col 97}{space 3}  .470857
{txt}{space 40}7  {c |}{col 44}{res}{space 2} .3623147{col 56}{space 2} .1811525{col 67}{space 1}    2.00{col 76}{space 3}0.048{col 84}{space 4} .0030825{col 97}{space 3} .7215469
{txt}{space 40}8  {c |}{col 44}{res}{space 2} .3074462{col 56}{space 2} .1414907{col 67}{space 1}    2.17{col 76}{space 3}0.032{col 84}{space 4} .0268649{col 97}{space 3} .5880276
{txt}{space 40}9  {c |}{col 44}{res}{space 2}-.0117461{col 56}{space 2} .0227187{col 67}{space 1}   -0.52{col 76}{space 3}0.606{col 84}{space 4}-.0567982{col 97}{space 3}  .033306
{txt}{space 39}10  {c |}{col 44}{res}{space 2} .2557055{col 56}{space 2} .1598908{col 67}{space 1}    1.60{col 76}{space 3}0.113{col 84}{space 4}-.0613639{col 97}{space 3} .5727748
{txt}{space 39}11  {c |}{col 44}{res}{space 2} .2171211{col 56}{space 2} .1174873{col 67}{space 1}    1.85{col 76}{space 3}0.067{col 84}{space 4}-.0158605{col 97}{space 3} .4501028
{txt}{space 39}12  {c |}{col 44}{res}{space 2}  .380575{col 56}{space 2} .1692472{col 67}{space 1}    2.25{col 76}{space 3}0.027{col 84}{space 4} .0449514{col 97}{space 3} .7161986
{txt}{space 39}13  {c |}{col 44}{res}{space 2} .3619917{col 56}{space 2} .1425064{col 67}{space 1}    2.54{col 76}{space 3}0.013{col 84}{space 4} .0793961{col 97}{space 3} .6445873
{txt}{space 39}14  {c |}{col 44}{res}{space 2} .1654661{col 56}{space 2} .1048512{col 67}{space 1}    1.58{col 76}{space 3}0.118{col 84}{space 4}-.0424577{col 97}{space 3} .3733899
{txt}{space 39}15  {c |}{col 44}{res}{space 2} .3056482{col 56}{space 2} .1158684{col 67}{space 1}    2.64{col 76}{space 3}0.010{col 84}{space 4} .0758768{col 97}{space 3} .5354197
{txt}{space 39}16  {c |}{col 44}{res}{space 2} .4812448{col 56}{space 2} .1956311{col 67}{space 1}    2.46{col 76}{space 3}0.016{col 84}{space 4}  .093301{col 97}{space 3} .8691887
{txt}{space 39}17  {c |}{col 44}{res}{space 2} .1347368{col 56}{space 2} .1561987{col 67}{space 1}    0.86{col 76}{space 3}0.390{col 84}{space 4} -.175011{col 97}{space 3} .4444846
{txt}{space 39}18  {c |}{col 44}{res}{space 2} .3607376{col 56}{space 2} .1517278{col 67}{space 1}    2.38{col 76}{space 3}0.019{col 84}{space 4} .0598556{col 97}{space 3} .6616196
{txt}{space 39}19  {c |}{col 44}{res}{space 2} .2262108{col 56}{space 2}  .097893{col 67}{space 1}    2.31{col 76}{space 3}0.023{col 84}{space 4} .0320854{col 97}{space 3} .4203363
{txt}{space 39}20  {c |}{col 44}{res}{space 2} .3103607{col 56}{space 2} .1579716{col 67}{space 1}    1.96{col 76}{space 3}0.052{col 84}{space 4}-.0029029{col 97}{space 3} .6236244
{txt}{space 39}21  {c |}{col 44}{res}{space 2}   .27349{col 56}{space 2} .1184096{col 67}{space 1}    2.31{col 76}{space 3}0.023{col 84}{space 4} .0386794{col 97}{space 3} .5083006
{txt}{space 39}22  {c |}{col 44}{res}{space 2} .2753465{col 56}{space 2}  .142564{col 67}{space 1}    1.93{col 76}{space 3}0.056{col 84}{space 4}-.0073632{col 97}{space 3} .5580563
{txt}{space 39}23  {c |}{col 44}{res}{space 2}-.0849525{col 56}{space 2} .0511495{col 67}{space 1}   -1.66{col 76}{space 3}0.100{col 84}{space 4}-.1863839{col 97}{space 3} .0164788
{txt}{space 39}24  {c |}{col 44}{res}{space 2}  .296914{col 56}{space 2} .0951666{col 67}{space 1}    3.12{col 76}{space 3}0.002{col 84}{space 4}  .108195{col 97}{space 3} .4856329
{txt}{space 39}25  {c |}{col 44}{res}{space 2} .1991615{col 56}{space 2} .1345216{col 67}{space 1}    1.48{col 76}{space 3}0.142{col 84}{space 4}-.0675998{col 97}{space 3} .4659228
{txt}{space 39}26  {c |}{col 44}{res}{space 2} .1060973{col 56}{space 2}  .109889{col 67}{space 1}    0.97{col 76}{space 3}0.337{col 84}{space 4}-.1118166{col 97}{space 3} .3240113
{txt}{space 39}27  {c |}{col 44}{res}{space 2} .3928329{col 56}{space 2}  .156292{col 67}{space 1}    2.51{col 76}{space 3}0.013{col 84}{space 4}    .0829{col 97}{space 3} .7027659
{txt}{space 39}28  {c |}{col 44}{res}{space 2} .0068282{col 56}{space 2} .0721453{col 67}{space 1}    0.09{col 76}{space 3}0.925{col 84}{space 4}-.1362387{col 97}{space 3} .1498951
{txt}{space 39}29  {c |}{col 44}{res}{space 2} .1131054{col 56}{space 2} .1295904{col 67}{space 1}    0.87{col 76}{space 3}0.385{col 84}{space 4}-.1438772{col 97}{space 3}  .370088
{txt}{space 39}30  {c |}{col 44}{res}{space 2} .1457145{col 56}{space 2} .1209162{col 67}{space 1}    1.21{col 76}{space 3}0.231{col 84}{space 4} -.094067{col 97}{space 3} .3854959
{txt}{space 39}31  {c |}{col 44}{res}{space 2}-.0120207{col 56}{space 2} .1450054{col 67}{space 1}   -0.08{col 76}{space 3}0.934{col 84}{space 4}-.2995718{col 97}{space 3} .2755305
{txt}{space 39}32  {c |}{col 44}{res}{space 2} .2557783{col 56}{space 2} .1122242{col 67}{space 1}    2.28{col 76}{space 3}0.025{col 84}{space 4} .0332336{col 97}{space 3}  .478323
{txt}{space 39}33  {c |}{col 44}{res}{space 2} .1542137{col 56}{space 2} .0687369{col 67}{space 1}    2.24{col 76}{space 3}0.027{col 84}{space 4} .0179059{col 97}{space 3} .2905215
{txt}{space 39}34  {c |}{col 44}{res}{space 2} .1584916{col 56}{space 2} .1189849{col 67}{space 1}    1.33{col 76}{space 3}0.186{col 84}{space 4}-.0774599{col 97}{space 3} .3944431
{txt}{space 39}35  {c |}{col 44}{res}{space 2} .1899045{col 56}{space 2} .0930942{col 67}{space 1}    2.04{col 76}{space 3}0.044{col 84}{space 4} .0052952{col 97}{space 3} .3745137
{txt}{space 39}36  {c |}{col 44}{res}{space 2} .2482487{col 56}{space 2} .1170149{col 67}{space 1}    2.12{col 76}{space 3}0.036{col 84}{space 4} .0162037{col 97}{space 3} .4802938
{txt}{space 39}37  {c |}{col 44}{res}{space 2}  .244901{col 56}{space 2} .1107954{col 67}{space 1}    2.21{col 76}{space 3}0.029{col 84}{space 4} .0251896{col 97}{space 3} .4646123
{txt}{space 39}38  {c |}{col 44}{res}{space 2} .3950838{col 56}{space 2} .1619577{col 67}{space 1}    2.44{col 76}{space 3}0.016{col 84}{space 4} .0739156{col 97}{space 3} .7162519
{txt}{space 39}39  {c |}{col 44}{res}{space 2} .2195978{col 56}{space 2} .1147429{col 67}{space 1}    1.91{col 76}{space 3}0.058{col 84}{space 4}-.0079417{col 97}{space 3} .4471374
{txt}{space 39}40  {c |}{col 44}{res}{space 2} .0324025{col 56}{space 2} .0715005{col 67}{space 1}    0.45{col 76}{space 3}0.651{col 84}{space 4}-.1093857{col 97}{space 3} .1741906
{txt}{space 39}41  {c |}{col 44}{res}{space 2} .3097574{col 56}{space 2} .1465858{col 67}{space 1}    2.11{col 76}{space 3}0.037{col 84}{space 4} .0190723{col 97}{space 3} .6004426
{txt}{space 39}42  {c |}{col 44}{res}{space 2} .3206178{col 56}{space 2} .1205696{col 67}{space 1}    2.66{col 76}{space 3}0.009{col 84}{space 4} .0815236{col 97}{space 3} .5597119
{txt}{space 39}43  {c |}{col 44}{res}{space 2} .1087069{col 56}{space 2} .0468596{col 67}{space 1}    2.32{col 76}{space 3}0.022{col 84}{space 4} .0157826{col 97}{space 3} .2016313
{txt}{space 39}44  {c |}{col 44}{res}{space 2} .3573042{col 56}{space 2} .1018166{col 67}{space 1}    3.51{col 76}{space 3}0.001{col 84}{space 4} .1553981{col 97}{space 3} .5592104
{txt}{space 39}45  {c |}{col 44}{res}{space 2} .3065609{col 56}{space 2}  .122286{col 67}{space 1}    2.51{col 76}{space 3}0.014{col 84}{space 4} .0640631{col 97}{space 3} .5490586
{txt}{space 39}46  {c |}{col 44}{res}{space 2} .2880128{col 56}{space 2} .1864175{col 67}{space 1}    1.54{col 76}{space 3}0.125{col 84}{space 4}-.0816601{col 97}{space 3} .6576856
{txt}{space 39}47  {c |}{col 44}{res}{space 2} .2062219{col 56}{space 2} .0855244{col 67}{space 1}    2.41{col 76}{space 3}0.018{col 84}{space 4} .0366238{col 97}{space 3} .3758201
{txt}{space 39}48  {c |}{col 44}{res}{space 2} .2328231{col 56}{space 2} .1326099{col 67}{space 1}    1.76{col 76}{space 3}0.082{col 84}{space 4}-.0301473{col 97}{space 3} .4957935
{txt}{space 39}49  {c |}{col 44}{res}{space 2} .4491372{col 56}{space 2} .1903848{col 67}{space 1}    2.36{col 76}{space 3}0.020{col 84}{space 4} .0715969{col 97}{space 3} .8266774
{txt}{space 39}50  {c |}{col 44}{res}{space 2} .4273724{col 56}{space 2} .1583739{col 67}{space 1}    2.70{col 76}{space 3}0.008{col 84}{space 4}  .113311{col 97}{space 3} .7414338
{txt}{space 39}51  {c |}{col 44}{res}{space 2} .3797878{col 56}{space 2} .1888108{col 67}{space 1}    2.01{col 76}{space 3}0.047{col 84}{space 4} .0053688{col 97}{space 3} .7542067
{txt}{space 39}52  {c |}{col 44}{res}{space 2} .3423464{col 56}{space 2} .1807856{col 67}{space 1}    1.89{col 76}{space 3}0.061{col 84}{space 4}-.0161582{col 97}{space 3} .7008509
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{txt}{space 39}55  {c |}{col 44}{res}{space 2} .5442383{col 56}{space 2} .2118891{col 67}{space 1}    2.57{col 76}{space 3}0.012{col 84}{space 4} .1240543{col 97}{space 3} .9644223
{txt}{space 39}56  {c |}{col 44}{res}{space 2} .3040157{col 56}{space 2}  .197895{col 67}{space 1}    1.54{col 76}{space 3}0.128{col 84}{space 4}-.0884175{col 97}{space 3} .6964488
{txt}{space 39}57  {c |}{col 44}{res}{space 2} .4111312{col 56}{space 2} .2287678{col 67}{space 1}    1.80{col 76}{space 3}0.075{col 84}{space 4} -.042524{col 97}{space 3} .8647863
{txt}{space 39}58  {c |}{col 44}{res}{space 2} .3017999{col 56}{space 2} .1499193{col 67}{space 1}    2.01{col 76}{space 3}0.047{col 84}{space 4} .0045043{col 97}{space 3} .5990955
{txt}{space 39}59  {c |}{col 44}{res}{space 2} .3431898{col 56}{space 2} .1696475{col 67}{space 1}    2.02{col 76}{space 3}0.046{col 84}{space 4} .0067725{col 97}{space 3} .6796071
{txt}{space 39}60  {c |}{col 44}{res}{space 2} .1853724{col 56}{space 2} .0927158{col 67}{space 1}    2.00{col 76}{space 3}0.048{col 84}{space 4} .0015134{col 97}{space 3} .3692314
{txt}{space 39}61  {c |}{col 44}{res}{space 2} .1893599{col 56}{space 2} .1059726{col 67}{space 1}    1.79{col 76}{space 3}0.077{col 84}{space 4}-.0207878{col 97}{space 3} .3995076
{txt}{space 39}62  {c |}{col 44}{res}{space 2} .4015776{col 56}{space 2} .1718611{col 67}{space 1}    2.34{col 76}{space 3}0.021{col 84}{space 4} .0607706{col 97}{space 3} .7423847
{txt}{space 39}63  {c |}{col 44}{res}{space 2} .4627491{col 56}{space 2} .1699935{col 67}{space 1}    2.72{col 76}{space 3}0.008{col 84}{space 4} .1256455{col 97}{space 3} .7998527
{txt}{space 39}64  {c |}{col 44}{res}{space 2} .4658617{col 56}{space 2} .1851072{col 67}{space 1}    2.52{col 76}{space 3}0.013{col 84}{space 4} .0987872{col 97}{space 3} .8329363
{txt}{space 39}65  {c |}{col 44}{res}{space 2} .2749976{col 56}{space 2}  .102043{col 67}{space 1}    2.69{col 76}{space 3}0.008{col 84}{space 4} .0726424{col 97}{space 3} .4773527
{txt}{space 39}66  {c |}{col 44}{res}{space 2} .3285775{col 56}{space 2}   .20252{col 67}{space 1}    1.62{col 76}{space 3}0.108{col 84}{space 4}-.0730271{col 97}{space 3} .7301822
{txt}{space 39}67  {c |}{col 44}{res}{space 2} .3334778{col 56}{space 2} .1311474{col 67}{space 1}    2.54{col 76}{space 3}0.012{col 84}{space 4} .0734075{col 97}{space 3}  .593548
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{txt}{space 39}69  {c |}{col 44}{res}{space 2} .1984599{col 56}{space 2} .1136135{col 67}{space 1}    1.75{col 76}{space 3}0.084{col 84}{space 4}-.0268399{col 97}{space 3} .4237598
{txt}{space 39}70  {c |}{col 44}{res}{space 2} .4171035{col 56}{space 2} .1856717{col 67}{space 1}    2.25{col 76}{space 3}0.027{col 84}{space 4} .0489096{col 97}{space 3} .7852975
{txt}{space 39}71  {c |}{col 44}{res}{space 2} .1210772{col 56}{space 2}  .136949{col 67}{space 1}    0.88{col 76}{space 3}0.379{col 84}{space 4}-.1504979{col 97}{space 3} .3926522
{txt}{space 39}72  {c |}{col 44}{res}{space 2} .2797371{col 56}{space 2} .1113298{col 67}{space 1}    2.51{col 76}{space 3}0.014{col 84}{space 4}  .058966{col 97}{space 3} .5005082
{txt}{space 39}73  {c |}{col 44}{res}{space 2} .4980197{col 56}{space 2} .1675033{col 67}{space 1}    2.97{col 76}{space 3}0.004{col 84}{space 4} .1658545{col 97}{space 3} .8301849
{txt}{space 39}74  {c |}{col 44}{res}{space 2} .0983883{col 56}{space 2} .1078386{col 67}{space 1}    0.91{col 76}{space 3}0.364{col 84}{space 4}-.1154597{col 97}{space 3} .3122364
{txt}{space 39}75  {c |}{col 44}{res}{space 2} .1962217{col 56}{space 2}  .126992{col 67}{space 1}    1.55{col 76}{space 3}0.125{col 84}{space 4}-.0556081{col 97}{space 3} .4480515
{txt}{space 39}76  {c |}{col 44}{res}{space 2} .3399951{col 56}{space 2} .1523745{col 67}{space 1}    2.23{col 76}{space 3}0.028{col 84}{space 4} .0378307{col 97}{space 3} .6421595
{txt}{space 39}77  {c |}{col 44}{res}{space 2} .2702073{col 56}{space 2} .1445737{col 67}{space 1}    1.87{col 76}{space 3}0.064{col 84}{space 4}-.0164878{col 97}{space 3} .5569024
{txt}{space 39}78  {c |}{col 44}{res}{space 2} .2997069{col 56}{space 2} .0981263{col 67}{space 1}    3.05{col 76}{space 3}0.003{col 84}{space 4} .1051187{col 97}{space 3} .4942951
{txt}{space 39}79  {c |}{col 44}{res}{space 2}-.0134479{col 56}{space 2} .0162857{col 67}{space 1}   -0.83{col 76}{space 3}0.411{col 84}{space 4}-.0457432{col 97}{space 3} .0188473
{txt}{space 39}80  {c |}{col 44}{res}{space 2} .4402289{col 56}{space 2} .1712619{col 67}{space 1}    2.57{col 76}{space 3}0.012{col 84}{space 4}   .10061{col 97}{space 3} .7798477
{txt}{space 39}81  {c |}{col 44}{res}{space 2} .2245002{col 56}{space 2} .1761132{col 67}{space 1}    1.27{col 76}{space 3}0.205{col 84}{space 4}-.1247389{col 97}{space 3} .5737394
{txt}{space 39}82  {c |}{col 44}{res}{space 2} .3624323{col 56}{space 2} .1830969{col 67}{space 1}    1.98{col 76}{space 3}0.050{col 84}{space 4}-.0006557{col 97}{space 3} .7255202
{txt}{space 39}83  {c |}{col 44}{res}{space 2} .4343327{col 56}{space 2} .1441956{col 67}{space 1}    3.01{col 76}{space 3}0.003{col 84}{space 4} .1483874{col 97}{space 3} .7202781
{txt}{space 39}84  {c |}{col 44}{res}{space 2} .3384269{col 56}{space 2} .1835023{col 67}{space 1}    1.84{col 76}{space 3}0.068{col 84}{space 4} -.025465{col 97}{space 3} .7023188
{txt}{space 39}85  {c |}{col 44}{res}{space 2}  .409473{col 56}{space 2} .1459018{col 67}{space 1}    2.81{col 76}{space 3}0.006{col 84}{space 4} .1201442{col 97}{space 3} .6988018
{txt}{space 39}86  {c |}{col 44}{res}{space 2} .4694255{col 56}{space 2} .1883438{col 67}{space 1}    2.49{col 76}{space 3}0.014{col 84}{space 4} .0959327{col 97}{space 3} .8429183
{txt}{space 39}87  {c |}{col 44}{res}{space 2} .4727653{col 56}{space 2} .1892157{col 67}{space 1}    2.50{col 76}{space 3}0.014{col 84}{space 4} .0975435{col 97}{space 3} .8479872
{txt}{space 39}88  {c |}{col 44}{res}{space 2} .2593307{col 56}{space 2} .1338827{col 67}{space 1}    1.94{col 76}{space 3}0.055{col 84}{space 4}-.0061637{col 97}{space 3}  .524825
{txt}{space 39}89  {c |}{col 44}{res}{space 2} .3043691{col 56}{space 2} .1448675{col 67}{space 1}    2.10{col 76}{space 3}0.038{col 84}{space 4} .0170913{col 97}{space 3} .5916469
{txt}{space 39}90  {c |}{col 44}{res}{space 2} .0808889{col 56}{space 2} .1083976{col 67}{space 1}    0.75{col 76}{space 3}0.457{col 84}{space 4}-.1340676{col 97}{space 3} .2958453
{txt}{space 39}91  {c |}{col 44}{res}{space 2} .1986179{col 56}{space 2} .1087834{col 67}{space 1}    1.83{col 76}{space 3}0.071{col 84}{space 4}-.0171036{col 97}{space 3} .4143394
{txt}{space 39}92  {c |}{col 44}{res}{space 2} .0812918{col 56}{space 2} .0443931{col 67}{space 1}    1.83{col 76}{space 3}0.070{col 84}{space 4}-.0067413{col 97}{space 3}  .169325
{txt}{space 39}93  {c |}{col 44}{res}{space 2} .4341582{col 56}{space 2} .1451825{col 67}{space 1}    2.99{col 76}{space 3}0.003{col 84}{space 4} .1462559{col 97}{space 3} .7220606
{txt}{space 39}94  {c |}{col 44}{res}{space 2} .4679822{col 56}{space 2} .1648801{col 67}{space 1}    2.84{col 76}{space 3}0.005{col 84}{space 4} .1410188{col 97}{space 3} .7949456
{txt}{space 39}95  {c |}{col 44}{res}{space 2}  .221372{col 56}{space 2} .1434216{col 67}{space 1}    1.54{col 76}{space 3}0.126{col 84}{space 4}-.0630384{col 97}{space 3} .5057825
{txt}{space 39}96  {c |}{col 44}{res}{space 2} .3468094{col 56}{space 2} .1529179{col 67}{space 1}    2.27{col 76}{space 3}0.025{col 84}{space 4} .0435676{col 97}{space 3} .6500513
{txt}{space 39}97  {c |}{col 44}{res}{space 2} .4022817{col 56}{space 2} .1471986{col 67}{space 1}    2.73{col 76}{space 3}0.007{col 84}{space 4} .1103814{col 97}{space 3} .6941821
{txt}{space 39}98  {c |}{col 44}{res}{space 2} .5649846{col 56}{space 2} .1823115{col 67}{space 1}    3.10{col 76}{space 3}0.002{col 84}{space 4}  .203454{col 97}{space 3} .9265152
{txt}{space 39}99  {c |}{col 44}{res}{space 2} .0924398{col 56}{space 2} .0915093{col 67}{space 1}    1.01{col 76}{space 3}0.315{col 84}{space 4}-.0890266{col 97}{space 3} .2739063
{txt}{space 38}100  {c |}{col 44}{res}{space 2} .2567187{col 56}{space 2} .1469718{col 67}{space 1}    1.75{col 76}{space 3}0.084{col 84}{space 4}-.0347319{col 97}{space 3} .5481693
{txt}{space 38}101  {c |}{col 44}{res}{space 2} .4099309{col 56}{space 2} .1328918{col 67}{space 1}    3.08{col 76}{space 3}0.003{col 84}{space 4} .1464015{col 97}{space 3} .6734603
{txt}{space 38}102  {c |}{col 44}{res}{space 2} .2555662{col 56}{space 2} .1527815{col 67}{space 1}    1.67{col 76}{space 3}0.097{col 84}{space 4}-.0474052{col 97}{space 3} .5585376
{txt}{space 38}103  {c |}{col 44}{res}{space 2} .0767007{col 56}{space 2} .1044287{col 67}{space 1}    0.73{col 76}{space 3}0.464{col 84}{space 4}-.1303853{col 97}{space 3} .2837866
{txt}{space 38}104  {c |}{col 44}{res}{space 2}-.0988051{col 56}{space 2} .0750391{col 67}{space 1}   -1.32{col 76}{space 3}0.191{col 84}{space 4}-.2476105{col 97}{space 3} .0500003
{txt}{space 38}105  {c |}{col 44}{res}{space 2} .3402825{col 56}{space 2} .1512284{col 67}{space 1}    2.25{col 76}{space 3}0.027{col 84}{space 4} .0403909{col 97}{space 3}  .640174
{txt}{space 42} {c |}
{space 38}year {c |}
{space 37}2011  {c |}{col 44}{res}{space 2}-.0040964{col 56}{space 2} .0032443{col 67}{space 1}   -1.26{col 76}{space 3}0.210{col 84}{space 4}-.0105299{col 97}{space 3} .0023371
{txt}{space 37}2012  {c |}{col 44}{res}{space 2}-.0001721{col 56}{space 2} .0045661{col 67}{space 1}   -0.04{col 76}{space 3}0.970{col 84}{space 4}-.0092269{col 97}{space 3} .0088827
{txt}{space 37}2013  {c |}{col 44}{res}{space 2}-.0012832{col 56}{space 2}   .00508{col 67}{space 1}   -0.25{col 76}{space 3}0.801{col 84}{space 4} -.011357{col 97}{space 3} .0087905
{txt}{space 37}2014  {c |}{col 44}{res}{space 2}-.0072834{col 56}{space 2} .0071466{col 67}{space 1}   -1.02{col 76}{space 3}0.310{col 84}{space 4}-.0214553{col 97}{space 3} .0068885
{txt}{space 37}2015  {c |}{col 44}{res}{space 2}-.0148492{col 56}{space 2} .0086411{col 67}{space 1}   -1.72{col 76}{space 3}0.089{col 84}{space 4}-.0319848{col 97}{space 3} .0022864
{txt}{space 37}2016  {c |}{col 44}{res}{space 2}-.0181348{col 56}{space 2} .0074617{col 67}{space 1}   -2.43{col 76}{space 3}0.017{col 84}{space 4}-.0329317{col 97}{space 3} -.003338
{txt}{space 37}2017  {c |}{col 44}{res}{space 2} -.003829{col 56}{space 2} .0096083{col 67}{space 1}   -0.40{col 76}{space 3}0.691{col 84}{space 4}-.0228826{col 97}{space 3} .0152245
{txt}{space 37}2018  {c |}{col 44}{res}{space 2}-.0329911{col 56}{space 2}  .007421{col 67}{space 1}   -4.45{col 76}{space 3}0.000{col 84}{space 4}-.0477072{col 97}{space 3}-.0182751
{txt}{space 37}2019  {c |}{col 44}{res}{space 2}-.0713199{col 56}{space 2} .0084778{col 67}{space 1}   -8.41{col 76}{space 3}0.000{col 84}{space 4}-.0881317{col 97}{space 3}-.0545082
{txt}{space 42} {c |}
{space 22}ln_ratio_fmsup_fmsub {c |}{col 44}{res}{space 2}        0{col 56}{txt}  (omitted)
{space 32}1.minority {c |}{col 44}{res}{space 2}        0{col 56}{txt}  (omitted)
{space 42} {c |}
{space 11}minority#c.ln_ratio_fmsup_fmsub {c |}
{space 40}1  {c |}{col 44}{res}{space 2}  .030916{col 56}{space 2} .0194418{col 67}{space 1}    1.59{col 76}{space 3}0.115{col 84}{space 4}-.0076379{col 97}{space 3} .0694699
{txt}{space 42} {c |}
{space 23}minority#supervisor {c |}
{space 38}1 1  {c |}{col 44}{res}{space 2}-.0036605{col 56}{space 2} .0106787{col 67}{space 1}   -0.34{col 76}{space 3}0.732{col 84}{space 4}-.0248368{col 97}{space 3} .0175158
{txt}{space 42} {c |}
minority#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 38}1 1  {c |}{col 44}{res}{space 2}-.0297201{col 56}{space 2} .0257136{col 67}{space 1}   -1.16{col 76}{space 3}0.250{col 84}{space 4}-.0807112{col 97}{space 3}  .021271
{txt}{space 42} {c |}
{space 37}_cons {c |}{col 44}{res}{space 2}-.1468542{col 56}{space 2} .4115397{col 67}{space 1}   -0.36{col 76}{space 3}0.722{col 84}{space 4}-.9629528{col 97}{space 3} .6692444
{txt}{hline 43}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891242{col 50}    24{col 58}  3782532{col 69}  3782837
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1275063{col 26}{space 2} .0448418{col 37}{space 1}    2.84{col 46}{space 3}0.005{col 54}{space 4} .0385833{col 67}{space 3} .2164292
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0048597{col 26}{space 2} .0261583{col 37}{space 1}    0.19{col 46}{space 3}0.853{col 54}{space 4}-.0470132{col 67}{space 3} .0567326
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1938778{col 26}{space 2} .0463535{col 37}{space 1}    4.18{col 46}{space 3}0.000{col 54}{space 4} .1019572{col 67}{space 3} .2857985
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.gender#c.ln_ratio_fmsup_fmsub +  1.gender#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.gender#c.ln_ratio_fmsup_fmsub + 1.gender#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0020101{col 26}{space 2} .0181757{col 37}{space 1}    0.11{col 46}{space 3}0.912{col 54}{space 4}-.0340331{col 67}{space 3} .0380533
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
. 
. 
. *** MODEL I6: Minority Absolute SGPD contagion for Women/Men Respondents as an Added Set of Covariates  -- CONTROLLING FOR GENDER SUPERVISORY EMPLOYEE IDENTITY GROUP DIFFERENTIAL ***
. 
. 
. regress lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year c.ln_ratio_mnmsup_mnmsub##i.gender##i.supervisor, vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_mnmsup_mnmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.gender} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(23, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0403
                                                {txt}Root MSE          =    {res} .51454

{txt}{ralign 110:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 45}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 46}{c |}{col 58}    Robust
{col 1}                         lndiversity2zeroadj{col 46}{c |} Coefficient{col 58}  std. err.{col 70}      t{col 78}   P>|t|{col 86}     [95% con{col 99}f. interval]
{hline 45}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 22}ln_ratio_mnmsup_mnmsub {c |}{col 46}{res}{space 2}   .04031{col 58}{space 2} .0339603{col 69}{space 1}    1.19{col 78}{space 3}0.238{col 86}{space 4}-.0270345{col 99}{space 3} .1076546
{txt}{space 34}1.minority {c |}{col 46}{res}{space 2}-.0819899{col 58}{space 2} .0066784{col 69}{space 1}  -12.28{col 78}{space 3}0.000{col 86}{space 4}-.0952334{col 99}{space 3}-.0687465
{txt}{space 44} {c |}
{space 11}minority#c.ln_ratio_mnmsup_mnmsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0403985{col 58}{space 2}     .018{col 69}{space 1}    2.24{col 78}{space 3}0.027{col 86}{space 4} .0047039{col 99}{space 3} .0760931
{txt}{space 44} {c |}
{space 32}1.supervisor {c |}{col 46}{res}{space 2} .1290534{col 58}{space 2} .0168735{col 69}{space 1}    7.65{col 78}{space 3}0.000{col 86}{space 4} .0955926{col 99}{space 3} .1625142
{txt}{space 44} {c |}
{space 9}supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0200797{col 58}{space 2} .0342856{col 69}{space 1}    0.59{col 78}{space 3}0.559{col 86}{space 4}-.0479098{col 99}{space 3} .0880693
{txt}{space 44} {c |}
{space 25}minority#supervisor {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0161039{col 58}{space 2}  .008136{col 69}{space 1}    1.98{col 78}{space 3}0.050{col 86}{space 4}  -.00003{col 99}{space 3} .0322378
{txt}{space 44} {c |}
minority#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0293602{col 58}{space 2}  .016461{col 69}{space 1}    1.78{col 78}{space 3}0.077{col 86}{space 4}-.0032827{col 99}{space 3} .0620031
{txt}{space 44} {c |}
{space 19}ln_ratio_min_tot_nmin_tot {c |}{col 46}{res}{space 2} .0539269{col 58}{space 2} .0450939{col 69}{space 1}    1.20{col 78}{space 3}0.234{col 86}{space 4}-.0354961{col 99}{space 3} .1433499
{txt}{space 38}gender {c |}{col 46}{res}{space 2}-.0349385{col 58}{space 2} .0088273{col 69}{space 1}   -3.96{col 78}{space 3}0.000{col 86}{space 4}-.0524434{col 99}{space 3}-.0174336
{txt}{space 28}topoffminority_2 {c |}{col 46}{res}{space 2} .0074835{col 58}{space 2}  .005921{col 69}{space 1}    1.26{col 78}{space 3}0.209{col 86}{space 4} -.004258{col 99}{space 3}  .019225
{txt}{space 24}lntotworkforce_count {c |}{col 46}{res}{space 2} .0649741{col 58}{space 2} .0402031{col 69}{space 1}    1.62{col 78}{space 3}0.109{col 86}{space 4}-.0147502{col 99}{space 3} .1446984
{txt}{space 16}ln_professionals_total_ratio {c |}{col 46}{res}{space 2} .0221307{col 58}{space 2} .0501187{col 69}{space 1}    0.44{col 78}{space 3}0.660{col 86}{space 4}-.0772565{col 99}{space 3}  .121518
{txt}{space 44} {c |}
{space 36}agencyid {c |}
{space 42}2  {c |}{col 46}{res}{space 2} .2122552{col 58}{space 2} .1223851{col 69}{space 1}    1.73{col 78}{space 3}0.086{col 86}{space 4} -.030439{col 99}{space 3} .4549493
{txt}{space 42}3  {c |}{col 46}{res}{space 2} .0328376{col 58}{space 2}  .054166{col 69}{space 1}    0.61{col 78}{space 3}0.546{col 86}{space 4}-.0745756{col 99}{space 3} .1402509
{txt}{space 42}4  {c |}{col 46}{res}{space 2} .2847554{col 58}{space 2} .1638076{col 69}{space 1}    1.74{col 78}{space 3}0.085{col 86}{space 4}-.0400813{col 99}{space 3} .6095921
{txt}{space 42}5  {c |}{col 46}{res}{space 2} .1680272{col 58}{space 2} .1272286{col 69}{space 1}    1.32{col 78}{space 3}0.190{col 86}{space 4}-.0842719{col 99}{space 3} .4203263
{txt}{space 42}6  {c |}{col 46}{res}{space 2} .1735822{col 58}{space 2} .1182659{col 69}{space 1}    1.47{col 78}{space 3}0.145{col 86}{space 4}-.0609436{col 99}{space 3}  .408108
{txt}{space 42}7  {c |}{col 46}{res}{space 2} .2441195{col 58}{space 2} .2171153{col 69}{space 1}    1.12{col 78}{space 3}0.263{col 86}{space 4}-.1864284{col 99}{space 3} .6746673
{txt}{space 42}8  {c |}{col 46}{res}{space 2} .2341942{col 58}{space 2} .1620983{col 69}{space 1}    1.44{col 78}{space 3}0.152{col 86}{space 4}-.0872528{col 99}{space 3} .5556411
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{txt}{space 39}2015  {c |}{col 46}{res}{space 2}-.0102599{col 58}{space 2}  .008019{col 69}{space 1}   -1.28{col 78}{space 3}0.204{col 86}{space 4} -.026162{col 99}{space 3} .0056421
{txt}{space 39}2016  {c |}{col 46}{res}{space 2}-.0131922{col 58}{space 2} .0079947{col 69}{space 1}   -1.65{col 78}{space 3}0.102{col 86}{space 4} -.029046{col 99}{space 3} .0026616
{txt}{space 39}2017  {c |}{col 46}{res}{space 2}-.0029645{col 58}{space 2} .0118156{col 69}{space 1}   -0.25{col 78}{space 3}0.802{col 86}{space 4}-.0263953{col 99}{space 3} .0204663
{txt}{space 39}2018  {c |}{col 46}{res}{space 2}-.0293793{col 58}{space 2}  .010783{col 69}{space 1}   -2.72{col 78}{space 3}0.008{col 86}{space 4}-.0507623{col 99}{space 3}-.0079963
{txt}{space 39}2019  {c |}{col 46}{res}{space 2}-.0685615{col 58}{space 2} .0121763{col 69}{space 1}   -5.63{col 78}{space 3}0.000{col 86}{space 4}-.0927076{col 99}{space 3}-.0444154
{txt}{space 44} {c |}
{space 22}ln_ratio_mnmsup_mnmsub {c |}{col 46}{res}{space 2}        0{col 58}{txt}  (omitted)
{space 36}1.gender {c |}{col 46}{res}{space 2}        0{col 58}{txt}  (omitted)
{space 44} {c |}
{space 13}gender#c.ln_ratio_mnmsup_mnmsub {c |}
{space 42}1  {c |}{col 46}{res}{space 2} .0185266{col 58}{space 2} .0166015{col 69}{space 1}    1.12{col 78}{space 3}0.267{col 86}{space 4}-.0143948{col 99}{space 3} .0514481
{txt}{space 44} {c |}
{space 27}gender#supervisor {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2} .0015179{col 58}{space 2} .0123209{col 69}{space 1}    0.12{col 78}{space 3}0.902{col 86}{space 4}-.0229149{col 99}{space 3} .0259506
{txt}{space 44} {c |}
{space 2}gender#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 40}1 1  {c |}{col 46}{res}{space 2}-.0183255{col 58}{space 2} .0251105{col 69}{space 1}   -0.73{col 78}{space 3}0.467{col 86}{space 4}-.0681206{col 99}{space 3} .0314696
{txt}{space 44} {c |}
{space 39}_cons {c |}{col 46}{res}{space 2} .0417989{col 58}{space 2} .5053438{col 69}{space 1}    0.08{col 78}{space 3}0.934{col 86}{space 4}-.9603169{col 99}{space 3} 1.043915
{txt}{hline 45}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891431{col 50}    24{col 58}  3782911{col 69}  3783216
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}   .04031{col 26}{space 2} .0339603{col 37}{space 1}    1.19{col 46}{space 3}0.238{col 54}{space 4}-.0270345{col 67}{space 3} .1076546
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0403985{col 26}{space 2}     .018{col 37}{space 1}    2.24{col 46}{space 3}0.027{col 54}{space 4} .0047039{col 67}{space 3} .0760931
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. 
. ** BY SUPERVISOR RESPONDENT: WITHIN-IDENTITY "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0603898{col 26}{space 2} .0426908{col 37}{space 1}    1.41{col 46}{space 3}0.160{col 54}{space 4}-.0242677{col 67}{space 3} .1450473
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub +  1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#c.ln_ratio_mnmsup_mnmsub + 1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0697587{col 26}{space 2} .0162992{col 37}{space 1}    4.28{col 46}{space 3}0.000{col 54}{space 4} .0374368{col 67}{space 3} .1020806
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES 
.  
. lincom  1.minority#c.ln_ratio_mnmsup_mnmsub +  1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0293602{col 26}{space 2}  .016461{col 37}{space 1}    1.78{col 46}{space 3}0.077{col 54}{space 4}-.0032827{col 67}{space 3} .0620031
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. *****************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
.    
. *** MODEL I7: Women Relative SGPD contagion for Minority/Non-Minority Respondents as an Added Set of Covariates -- HETEROGENOUS WOMEN & MINORITY REPSONDENT EFFECTS ***
. 
. 
. regress lndiversity2zeroadj  c.ln_ratio_fmsup_fmsub##i.women_het##i.supervisor   ln_ratio_fem_tot_men_tot   minority   topoffgender_2 lntotworkforce_count  ln_professionals_total_ratio   i.agencyid i.year c.ln_ratio_fmsup_fmsub##i.minority_het##i.supervisor, vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_fmsup_fmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.minority_het} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.minority_het} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.minority_het#c.ln_ratio_fmsup_fmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.minority_het#1.supervisor} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:2.minority_het#1.supervisor#c.ln_ratio_fmsup_fmsub} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(27, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0408
                                                {txt}Root MSE          =    {res} .51443

{txt}{ralign 112:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 47}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 48}{c |}{col 60}    Robust
{col 1}                           lndiversity2zeroadj{col 48}{c |} Coefficient{col 60}  std. err.{col 72}      t{col 80}   P>|t|{col 88}     [95% con{col 101}f. interval]
{hline 47}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 26}ln_ratio_fmsup_fmsub {c |}{col 48}{res}{space 2} .1251451{col 60}{space 2}  .045272{col 71}{space 1}    2.76{col 80}{space 3}0.007{col 88}{space 4} .0353691{col 101}{space 3} .2149212
{txt}{space 46} {c |}
{space 37}women_het {c |}
{space 44}1  {c |}{col 48}{res}{space 2}-.0230248{col 60}{space 2} .0118941{col 71}{space 1}   -1.94{col 80}{space 3}0.056{col 88}{space 4}-.0466112{col 101}{space 3} .0005617
{txt}{space 44}2  {c |}{col 48}{res}{space 2}-.0657362{col 60}{space 2} .0094207{col 71}{space 1}   -6.98{col 80}{space 3}0.000{col 88}{space 4}-.0844177{col 101}{space 3}-.0470547
{txt}{space 46} {c |}
{space 14}women_het#c.ln_ratio_fmsup_fmsub {c |}
{space 44}1  {c |}{col 48}{res}{space 2} .0120584{col 60}{space 2} .0294514{col 71}{space 1}    0.41{col 80}{space 3}0.683{col 88}{space 4}-.0463448{col 101}{space 3} .0704616
{txt}{space 44}2  {c |}{col 48}{res}{space 2} .0359521{col 60}{space 2}  .031831{col 71}{space 1}    1.13{col 80}{space 3}0.261{col 88}{space 4}-.0271699{col 101}{space 3} .0990742
{txt}{space 46} {c |}
{space 34}1.supervisor {c |}{col 48}{res}{space 2} .1492795{col 60}{space 2} .0202652{col 71}{space 1}    7.37{col 80}{space 3}0.000{col 88}{space 4} .1090928{col 101}{space 3} .1894662
{txt}{space 46} {c |}
{space 13}supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 44}1  {c |}{col 48}{res}{space 2} .0657958{col 60}{space 2} .0401748{col 71}{space 1}    1.64{col 80}{space 3}0.104{col 88}{space 4}-.0138723{col 101}{space 3} .1454639
{txt}{space 46} {c |}
{space 26}women_het#supervisor {c |}
{space 42}1 1  {c |}{col 48}{res}{space 2}  .000701{col 60}{space 2} .0128219{col 71}{space 1}    0.05{col 80}{space 3}0.957{col 88}{space 4}-.0247253{col 101}{space 3} .0261273
{txt}{space 42}2 1  {c |}{col 48}{res}{space 2}-.0009958{col 60}{space 2} .0202678{col 71}{space 1}   -0.05{col 80}{space 3}0.961{col 88}{space 4}-.0411876{col 101}{space 3}  .039196
{txt}{space 46} {c |}
{space 3}women_het#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 42}1 1  {c |}{col 48}{res}{space 2}-.0014272{col 60}{space 2} .0277897{col 71}{space 1}   -0.05{col 80}{space 3}0.959{col 88}{space 4}-.0565353{col 101}{space 3} .0536809
{txt}{space 42}2 1  {c |}{col 48}{res}{space 2}-.0352263{col 60}{space 2}  .041707{col 71}{space 1}   -0.84{col 80}{space 3}0.400{col 88}{space 4}-.1179328{col 101}{space 3} .0474802
{txt}{space 46} {c |}
{space 22}ln_ratio_fem_tot_men_tot {c |}{col 48}{res}{space 2}-.0066919{col 60}{space 2} .0554615{col 71}{space 1}   -0.12{col 80}{space 3}0.904{col 88}{space 4} -.116674{col 101}{space 3} .1032903
{txt}{space 38}minority {c |}{col 48}{res}{space 2}-.0645354{col 60}{space 2} .0083952{col 71}{space 1}   -7.69{col 80}{space 3}0.000{col 88}{space 4}-.0811833{col 101}{space 3}-.0478875
{txt}{space 32}topoffgender_2 {c |}{col 48}{res}{space 2} -.002846{col 60}{space 2} .0045022{col 71}{space 1}   -0.63{col 80}{space 3}0.529{col 88}{space 4}-.0117739{col 101}{space 3}  .006082
{txt}{space 26}lntotworkforce_count {c |}{col 48}{res}{space 2} .0761761{col 60}{space 2} .0320721{col 71}{space 1}    2.38{col 80}{space 3}0.019{col 88}{space 4}  .012576{col 101}{space 3} .1397763
{txt}{space 18}ln_professionals_total_ratio {c |}{col 48}{res}{space 2} .0070453{col 60}{space 2} .0412842{col 71}{space 1}    0.17{col 80}{space 3}0.865{col 88}{space 4}-.0748228{col 101}{space 3} .0889133
{txt}{space 46} {c |}
{space 38}agencyid {c |}
{space 44}2  {c |}{col 48}{res}{space 2} .3142498{col 60}{space 2} .1132634{col 71}{space 1}    2.77{col 80}{space 3}0.007{col 88}{space 4} .0896442{col 101}{space 3} .5388555
{txt}{space 44}3  {c |}{col 48}{res}{space 2}  .093515{col 60}{space 2} .0534782{col 71}{space 1}    1.75{col 80}{space 3}0.083{col 88}{space 4}-.0125342{col 101}{space 3} .1995643
{txt}{space 44}4  {c |}{col 48}{res}{space 2} .4384041{col 60}{space 2} .1486901{col 71}{space 1}    2.95{col 80}{space 3}0.004{col 88}{space 4}  .143546{col 101}{space 3} .7332622
{txt}{space 44}5  {c |}{col 48}{res}{space 2}  .266754{col 60}{space 2} .1033559{col 71}{space 1}    2.58{col 80}{space 3}0.011{col 88}{space 4} .0617953{col 101}{space 3} .4717126
{txt}{space 44}6  {c |}{col 48}{res}{space 2} .2526579{col 60}{space 2} .1097969{col 71}{space 1}    2.30{col 80}{space 3}0.023{col 88}{space 4} .0349264{col 101}{space 3} .4703893
{txt}{space 44}7  {c |}{col 48}{res}{space 2}  .362806{col 60}{space 2} .1810394{col 71}{space 1}    2.00{col 80}{space 3}0.048{col 88}{space 4} .0037981{col 101}{space 3}  .721814
{txt}{space 44}8  {c |}{col 48}{res}{space 2} .3067517{col 60}{space 2}  .141421{col 71}{space 1}    2.17{col 80}{space 3}0.032{col 88}{space 4} .0263086{col 101}{space 3} .5871948
{txt}{space 44}9  {c |}{col 48}{res}{space 2}-.0119741{col 60}{space 2} .0227605{col 71}{space 1}   -0.53{col 80}{space 3}0.600{col 88}{space 4} -.057109{col 101}{space 3} .0331609
{txt}{space 43}10  {c |}{col 48}{res}{space 2} .2537971{col 60}{space 2}  .159854{col 71}{space 1}    1.59{col 80}{space 3}0.115{col 88}{space 4}-.0631993{col 101}{space 3} .5707936
{txt}{space 43}11  {c |}{col 48}{res}{space 2} .2159586{col 60}{space 2} .1174636{col 71}{space 1}    1.84{col 80}{space 3}0.069{col 88}{space 4}-.0169762{col 101}{space 3} .4488934
{txt}{space 43}12  {c |}{col 48}{res}{space 2} .3795504{col 60}{space 2} .1691389{col 71}{space 1}    2.24{col 80}{space 3}0.027{col 88}{space 4} .0441417{col 101}{space 3} .7149591
{txt}{space 43}13  {c |}{col 48}{res}{space 2} .3617835{col 60}{space 2} .1424788{col 71}{space 1}    2.54{col 80}{space 3}0.013{col 88}{space 4} .0792427{col 101}{space 3} .6443242
{txt}{space 43}14  {c |}{col 48}{res}{space 2} .1654758{col 60}{space 2} .1048937{col 71}{space 1}    1.58{col 80}{space 3}0.118{col 88}{space 4}-.0425324{col 101}{space 3} .3734841
{txt}{space 43}15  {c |}{col 48}{res}{space 2}  .303815{col 60}{space 2}   .11578{col 71}{space 1}    2.62{col 80}{space 3}0.010{col 88}{space 4}  .074219{col 101}{space 3} .5334111
{txt}{space 43}16  {c |}{col 48}{res}{space 2} .4838201{col 60}{space 2} .1955678{col 71}{space 1}    2.47{col 80}{space 3}0.015{col 88}{space 4} .0960017{col 101}{space 3} .8716385
{txt}{space 43}17  {c |}{col 48}{res}{space 2} .1334779{col 60}{space 2} .1562514{col 71}{space 1}    0.85{col 80}{space 3}0.395{col 88}{space 4}-.1763745{col 101}{space 3} .4433303
{txt}{space 43}18  {c |}{col 48}{res}{space 2} .3600461{col 60}{space 2} .1516814{col 71}{space 1}    2.37{col 80}{space 3}0.019{col 88}{space 4} .0592562{col 101}{space 3} .6608359
{txt}{space 43}19  {c |}{col 48}{res}{space 2} .2256626{col 60}{space 2} .0978964{col 71}{space 1}    2.31{col 80}{space 3}0.023{col 88}{space 4} .0315304{col 101}{space 3} .4197948
{txt}{space 43}20  {c |}{col 48}{res}{space 2} .3101598{col 60}{space 2} .1580542{col 71}{space 1}    1.96{col 80}{space 3}0.052{col 88}{space 4}-.0032676{col 101}{space 3} .6235871
{txt}{space 43}21  {c |}{col 48}{res}{space 2} .2720815{col 60}{space 2} .1183601{col 71}{space 1}    2.30{col 80}{space 3}0.024{col 88}{space 4} .0373691{col 101}{space 3}  .506794
{txt}{space 43}22  {c |}{col 48}{res}{space 2} .2749493{col 60}{space 2} .1424987{col 71}{space 1}    1.93{col 80}{space 3}0.056{col 88}{space 4}-.0076309{col 101}{space 3} .5575295
{txt}{space 43}23  {c |}{col 48}{res}{space 2}-.0872377{col 60}{space 2} .0512625{col 71}{space 1}   -1.70{col 80}{space 3}0.092{col 88}{space 4}-.1888931{col 101}{space 3} .0144177
{txt}{space 43}24  {c |}{col 48}{res}{space 2} .2967256{col 60}{space 2}  .095118{col 71}{space 1}    3.12{col 80}{space 3}0.002{col 88}{space 4}  .108103{col 101}{space 3} .4853482
{txt}{space 43}25  {c |}{col 48}{res}{space 2} .1976436{col 60}{space 2} .1346108{col 71}{space 1}    1.47{col 80}{space 3}0.145{col 88}{space 4}-.0692946{col 101}{space 3} .4645818
{txt}{space 43}26  {c |}{col 48}{res}{space 2} .1049814{col 60}{space 2} .1098752{col 71}{space 1}    0.96{col 80}{space 3}0.342{col 88}{space 4}-.1129052{col 101}{space 3}  .322868
{txt}{space 43}27  {c |}{col 48}{res}{space 2} .3922616{col 60}{space 2} .1562461{col 71}{space 1}    2.51{col 80}{space 3}0.014{col 88}{space 4} .0824197{col 101}{space 3} .7021036
{txt}{space 43}28  {c |}{col 48}{res}{space 2} .0051193{col 60}{space 2} .0721563{col 71}{space 1}    0.07{col 80}{space 3}0.944{col 88}{space 4}-.1379694{col 101}{space 3} .1482079
{txt}{space 43}29  {c |}{col 48}{res}{space 2} .1117205{col 60}{space 2} .1295789{col 71}{space 1}    0.86{col 80}{space 3}0.391{col 88}{space 4}-.1452393{col 101}{space 3} .3686804
{txt}{space 43}30  {c |}{col 48}{res}{space 2} .1454035{col 60}{space 2} .1209093{col 71}{space 1}    1.20{col 80}{space 3}0.232{col 88}{space 4}-.0943642{col 101}{space 3} .3851711
{txt}{space 43}31  {c |}{col 48}{res}{space 2}-.0137948{col 60}{space 2}  .145135{col 71}{space 1}   -0.10{col 80}{space 3}0.924{col 88}{space 4} -.301603{col 101}{space 3} .2740134
{txt}{space 43}32  {c |}{col 48}{res}{space 2} .2543017{col 60}{space 2} .1122059{col 71}{space 1}    2.27{col 80}{space 3}0.025{col 88}{space 4} .0317931{col 101}{space 3} .4768103
{txt}{space 43}33  {c |}{col 48}{res}{space 2} .1530291{col 60}{space 2} .0687297{col 71}{space 1}    2.23{col 80}{space 3}0.028{col 88}{space 4} .0167357{col 101}{space 3} .2893226
{txt}{space 43}34  {c |}{col 48}{res}{space 2} .1596566{col 60}{space 2} .1189806{col 71}{space 1}    1.34{col 80}{space 3}0.183{col 88}{space 4}-.0762864{col 101}{space 3} .3955997
{txt}{space 43}35  {c |}{col 48}{res}{space 2} .1888652{col 60}{space 2} .0930326{col 71}{space 1}    2.03{col 80}{space 3}0.045{col 88}{space 4}  .004378{col 101}{space 3} .3733524
{txt}{space 43}36  {c |}{col 48}{res}{space 2} .2474227{col 60}{space 2} .1170175{col 71}{space 1}    2.11{col 80}{space 3}0.037{col 88}{space 4} .0153727{col 101}{space 3} .4794727
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{txt}{space 46} {c |}
{space 42}year {c |}
{space 41}2011  {c |}{col 48}{res}{space 2}-.0041407{col 60}{space 2}  .003243{col 71}{space 1}   -1.28{col 80}{space 3}0.205{col 88}{space 4}-.0105717{col 101}{space 3} .0022903
{txt}{space 41}2012  {c |}{col 48}{res}{space 2}-.0002958{col 60}{space 2} .0045518{col 71}{space 1}   -0.06{col 80}{space 3}0.948{col 88}{space 4}-.0093221{col 101}{space 3} .0087305
{txt}{space 41}2013  {c |}{col 48}{res}{space 2}-.0013542{col 60}{space 2} .0050748{col 71}{space 1}   -0.27{col 80}{space 3}0.790{col 88}{space 4}-.0114178{col 101}{space 3} .0087094
{txt}{space 41}2014  {c |}{col 48}{res}{space 2}-.0073764{col 60}{space 2} .0071412{col 71}{space 1}   -1.03{col 80}{space 3}0.304{col 88}{space 4}-.0215377{col 101}{space 3} .0067849
{txt}{space 41}2015  {c |}{col 48}{res}{space 2}-.0149338{col 60}{space 2} .0086321{col 71}{space 1}   -1.73{col 80}{space 3}0.087{col 88}{space 4}-.0320516{col 101}{space 3}  .002184
{txt}{space 41}2016  {c |}{col 48}{res}{space 2}-.0182919{col 60}{space 2} .0074657{col 71}{space 1}   -2.45{col 80}{space 3}0.016{col 88}{space 4}-.0330965{col 101}{space 3}-.0034872
{txt}{space 41}2017  {c |}{col 48}{res}{space 2}-.0039086{col 60}{space 2} .0096237{col 71}{space 1}   -0.41{col 80}{space 3}0.685{col 88}{space 4}-.0229928{col 101}{space 3} .0151756
{txt}{space 41}2018  {c |}{col 48}{res}{space 2}-.0331116{col 60}{space 2} .0074263{col 71}{space 1}   -4.46{col 80}{space 3}0.000{col 88}{space 4}-.0478383{col 101}{space 3}-.0183849
{txt}{space 41}2019  {c |}{col 48}{res}{space 2}-.0714085{col 60}{space 2} .0084836{col 71}{space 1}   -8.42{col 80}{space 3}0.000{col 88}{space 4}-.0882317{col 101}{space 3}-.0545853
{txt}{space 46} {c |}
{space 26}ln_ratio_fmsup_fmsub {c |}{col 48}{res}{space 2}        0{col 60}{txt}  (omitted)
{space 46} {c |}
{space 34}minority_het {c |}
{space 44}1  {c |}{col 48}{res}{space 2}        0{col 60}{txt}  (omitted)
{space 44}2  {c |}{col 48}{res}{space 2}        0{col 60}{txt}  (omitted)
{space 46} {c |}
{space 11}minority_het#c.ln_ratio_fmsup_fmsub {c |}
{space 44}1  {c |}{col 48}{res}{space 2} .0344857{col 60}{space 2} .0204368{col 71}{space 1}    1.69{col 80}{space 3}0.095{col 88}{space 4}-.0060412{col 101}{space 3} .0750126
{txt}{space 44}2  {c |}{col 48}{res}{space 2}        0{col 60}{txt}  (omitted)
{space 46} {c |}
{space 23}minority_het#supervisor {c |}
{space 42}1 1  {c |}{col 48}{res}{space 2}-.0093626{col 60}{space 2} .0112795{col 71}{space 1}   -0.83{col 80}{space 3}0.408{col 88}{space 4}-.0317303{col 101}{space 3} .0130051
{txt}{space 42}2 1  {c |}{col 48}{res}{space 2}        0{col 60}{txt}  (omitted)
{space 46} {c |}
minority_het#supervisor#c.ln_ratio_fmsup_fmsub {c |}
{space 42}1 1  {c |}{col 48}{res}{space 2}-.0214867{col 60}{space 2} .0266562{col 71}{space 1}   -0.81{col 80}{space 3}0.422{col 88}{space 4}-.0743469{col 101}{space 3} .0313736
{txt}{space 42}2 1  {c |}{col 48}{res}{space 2}        0{col 60}{txt}  (omitted)
{space 46} {c |}
{space 41}_cons {c |}{col 48}{res}{space 2}-.1516694{col 60}{space 2} .4117522{col 71}{space 1}   -0.37{col 80}{space 3}0.713{col 88}{space 4}-.9681893{col 101}{space 3} .6648506
{txt}{hline 47}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1890891{col 50}    28{col 58}  3781839{col 69}  3782196
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN GENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1251451{col 26}{space 2}  .045272{col 37}{space 1}    2.76{col 46}{space 3}0.007{col 54}{space 4} .0353691{col 67}{space 3} .2149212
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0120584{col 26}{space 2} .0294514{col 37}{space 1}    0.41{col 46}{space 3}0.683{col 54}{space 4}-.0463448{col 67}{space 3} .0704616
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0359521{col 26}{space 2}  .031831{col 37}{space 1}    1.13{col 46}{space 3}0.261{col 54}{space 4}-.0271699{col 67}{space 3} .0990742
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom 2.women_het#c.ln_ratio_fmsup_fmsub -  1.women_het#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0238937{col 26}{space 2} .0195261{col 37}{space 1}    1.22{col 46}{space 3}0.224{col 54}{space 4}-.0148273{col 67}{space 3} .0626147
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT:BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEENGENDERED RESPONDENTS **
. 
. lincom c.ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_fmsup_fmsub + 1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .1909409{col 26}{space 2} .0458205{col 37}{space 1}    4.17{col 46}{space 3}0.000{col 54}{space 4} .1000771{col 67}{space 3} .2818048
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#c.ln_ratio_fmsup_fmsub + 1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0106312{col 26}{space 2} .0153654{col 37}{space 1}    0.69{col 46}{space 3}0.491{col 54}{space 4}-.0198389{col 67}{space 3} .0411013
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0007259{col 26}{space 2} .0355335{col 37}{space 1}    0.02{col 46}{space 3}0.984{col 54}{space 4}-.0697384{col 67}{space 3} .0711901
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub - (1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.women_het#c.ln_ratio_fmsup_fmsub + 2.women_het#c.ln_ratio_fmsup_fmsub - 1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub + 2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0099054{col 26}{space 2}  .030213{col 37}{space 1}   -0.33{col 46}{space 3}0.744{col 54}{space 4}-.0698189{col 67}{space 3} .0500082
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG WOMEN RESPONDENT DIFFERENCES [NON-MINORITY WOMEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.women_het#c.ln_ratio_fmsup_fmsub +  1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub  - (1.women_het#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0014272{col 26}{space 2} .0277897{col 37}{space 1}   -0.05{col 46}{space 3}0.959{col 54}{space 4}-.0565353{col 67}{space 3} .0536809
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.women_het#c.ln_ratio_fmsup_fmsub +  2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub  - (2.women_het#c.ln_ratio_fmsup_fmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.women_het#1.supervisor#c.ln_ratio_fmsup_fmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0352263{col 26}{space 2}  .041707{col 37}{space 1}   -0.84{col 46}{space 3}0.400{col 54}{space 4}-.1179328{col 67}{space 3} .0474802
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. 
. 
. 
. 
. 
.    
. *** MODEL I8: Minority Relative SGPD contagion for Women/Men Respondents as an Added Set of Covariates -- HETEROGENOUS WOMEN & MINORITY REPSONDENT EFFECTS  ***
. 
. regress  lndiversity2zeroadj  c.ln_ratio_mnmsup_mnmsub##i.minority_het##i.supervisor  ln_ratio_min_tot_nmin_tot   gender  topoffminority_2 lntotworkforce_count  ln_professionals_total_ratio  i.agencyid i.year c.ln_ratio_mnmsup_mnmsub##i.gender##i.supervisor  if e(sample), vce(cluster agencyid)
{txt}{p 0 6 2}note: {bf:ln_ratio_mnmsup_mnmsub} omitted because of collinearity.{p_end}
{p 0 6 2}note: {bf:1.gender} omitted because of collinearity.{p_end}

Linear regression                               Number of obs     = {res} 2,507,103
                                                {txt}{help j_robustsingular:F(27, 104) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.0406
                                                {txt}Root MSE          =    {res} .51447

{txt}{ralign 114:(Std. err. adjusted for {res:105} clusters in {res:agencyid})}
{hline 49}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 50}{c |}{col 62}    Robust
{col 1}                             lndiversity2zeroadj{col 50}{c |} Coefficient{col 62}  std. err.{col 74}      t{col 82}   P>|t|{col 90}     [95% con{col 103}f. interval]
{hline 49}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 26}ln_ratio_mnmsup_mnmsub {c |}{col 50}{res}{space 2} .0471792{col 62}{space 2} .0345551{col 73}{space 1}    1.37{col 82}{space 3}0.175{col 90}{space 4}-.0213448{col 103}{space 3} .1157032
{txt}{space 48} {c |}
{space 36}minority_het {c |}
{space 46}1  {c |}{col 50}{res}{space 2}-.0702077{col 62}{space 2} .0070793{col 73}{space 1}   -9.92{col 82}{space 3}0.000{col 90}{space 4}-.0842462{col 103}{space 3}-.0561692
{txt}{space 46}2  {c |}{col 50}{res}{space 2}-.0981746{col 62}{space 2} .0079877{col 73}{space 1}  -12.29{col 82}{space 3}0.000{col 90}{space 4}-.1140145{col 103}{space 3}-.0823348
{txt}{space 48} {c |}
{space 11}minority_het#c.ln_ratio_mnmsup_mnmsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2} .0189138{col 62}{space 2} .0198446{col 73}{space 1}    0.95{col 82}{space 3}0.343{col 90}{space 4}-.0204388{col 103}{space 3} .0582664
{txt}{space 46}2  {c |}{col 50}{res}{space 2} .0487378{col 62}{space 2} .0185456{col 73}{space 1}    2.63{col 82}{space 3}0.010{col 90}{space 4} .0119611{col 103}{space 3} .0855145
{txt}{space 48} {c |}
{space 36}1.supervisor {c |}{col 50}{res}{space 2}   .13009{col 62}{space 2} .0168177{col 73}{space 1}    7.74{col 82}{space 3}0.000{col 90}{space 4} .0967399{col 103}{space 3} .1634402
{txt}{space 48} {c |}
{space 13}supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2} .0128798{col 62}{space 2}  .033757{col 73}{space 1}    0.38{col 82}{space 3}0.704{col 90}{space 4}-.0540617{col 103}{space 3} .0798213
{txt}{space 48} {c |}
{space 25}minority_het#supervisor {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2} .0138398{col 62}{space 2} .0073868{col 73}{space 1}    1.87{col 82}{space 3}0.064{col 90}{space 4}-.0008085{col 103}{space 3} .0284881
{txt}{space 44}2 1  {c |}{col 50}{res}{space 2} .0150222{col 62}{space 2} .0127109{col 73}{space 1}    1.18{col 82}{space 3}0.240{col 90}{space 4} -.010184{col 103}{space 3} .0402285
{txt}{space 48} {c |}
minority_het#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2} .0487715{col 62}{space 2} .0166907{col 73}{space 1}    2.92{col 82}{space 3}0.004{col 90}{space 4} .0156733{col 103}{space 3} .0818697
{txt}{space 44}2 1  {c |}{col 50}{res}{space 2} .0155334{col 62}{space 2} .0249986{col 73}{space 1}    0.62{col 82}{space 3}0.536{col 90}{space 4}-.0340397{col 103}{space 3} .0651065
{txt}{space 48} {c |}
{space 23}ln_ratio_min_tot_nmin_tot {c |}{col 50}{res}{space 2} .0538545{col 62}{space 2} .0451184{col 73}{space 1}    1.19{col 82}{space 3}0.235{col 90}{space 4}-.0356171{col 103}{space 3}  .143326
{txt}{space 42}gender {c |}{col 50}{res}{space 2}-.0248245{col 62}{space 2} .0102179{col 73}{space 1}   -2.43{col 82}{space 3}0.017{col 90}{space 4} -.045087{col 103}{space 3}-.0045621
{txt}{space 32}topoffminority_2 {c |}{col 50}{res}{space 2} .0074886{col 62}{space 2} .0059282{col 73}{space 1}    1.26{col 82}{space 3}0.209{col 90}{space 4}-.0042673{col 103}{space 3} .0192445
{txt}{space 28}lntotworkforce_count {c |}{col 50}{res}{space 2}  .064715{col 62}{space 2} .0402298{col 73}{space 1}    1.61{col 82}{space 3}0.111{col 90}{space 4}-.0150622{col 103}{space 3} .1444922
{txt}{space 20}ln_professionals_total_ratio {c |}{col 50}{res}{space 2} .0220044{col 62}{space 2}   .05015{col 73}{space 1}    0.44{col 82}{space 3}0.662{col 90}{space 4} -.077445{col 103}{space 3} .1214538
{txt}{space 48} {c |}
{space 40}agencyid {c |}
{space 46}2  {c |}{col 50}{res}{space 2} .2107431{col 62}{space 2} .1224999{col 73}{space 1}    1.72{col 82}{space 3}0.088{col 90}{space 4}-.0321789{col 103}{space 3}  .453665
{txt}{space 46}3  {c |}{col 50}{res}{space 2} .0312314{col 62}{space 2} .0542469{col 73}{space 1}    0.58{col 82}{space 3}0.566{col 90}{space 4}-.0763422{col 103}{space 3} .1388051
{txt}{space 46}4  {c |}{col 50}{res}{space 2} .2818578{col 62}{space 2} .1639104{col 73}{space 1}    1.72{col 82}{space 3}0.088{col 90}{space 4}-.0431826{col 103}{space 3} .6068982
{txt}{space 46}5  {c |}{col 50}{res}{space 2} .1674135{col 62}{space 2} .1272974{col 73}{space 1}    1.32{col 82}{space 3}0.191{col 90}{space 4}-.0850219{col 103}{space 3}  .419849
{txt}{space 46}6  {c |}{col 50}{res}{space 2} .1720309{col 62}{space 2} .1185014{col 73}{space 1}    1.45{col 82}{space 3}0.150{col 90}{space 4}-.0629619{col 103}{space 3} .4070236
{txt}{space 46}7  {c |}{col 50}{res}{space 2} .2441181{col 62}{space 2} .2171694{col 73}{space 1}    1.12{col 82}{space 3}0.264{col 90}{space 4}-.1865369{col 103}{space 3} .6747731
{txt}{space 46}8  {c |}{col 50}{res}{space 2} .2330418{col 62}{space 2} .1621932{col 73}{space 1}    1.44{col 82}{space 3}0.154{col 90}{space 4}-.0885935{col 103}{space 3}  .554677
{txt}{space 46}9  {c |}{col 50}{res}{space 2} -.055742{col 62}{space 2} .0229419{col 73}{space 1}   -2.43{col 82}{space 3}0.017{col 90}{space 4}-.1012367{col 103}{space 3}-.0102474
{txt}{space 45}10  {c |}{col 50}{res}{space 2} .1884584{col 62}{space 2} .2310828{col 73}{space 1}    0.82{col 82}{space 3}0.417{col 90}{space 4}-.2697875{col 103}{space 3} .6467044
{txt}{space 45}11  {c |}{col 50}{res}{space 2} .1584321{col 62}{space 2} .1049441{col 73}{space 1}    1.51{col 82}{space 3}0.134{col 90}{space 4} -.049676{col 103}{space 3} .3665402
{txt}{space 45}12  {c |}{col 50}{res}{space 2} .3162592{col 62}{space 2} .2143917{col 73}{space 1}    1.48{col 82}{space 3}0.143{col 90}{space 4}-.1088876{col 103}{space 3} .7414059
{txt}{space 45}13  {c |}{col 50}{res}{space 2} .3125717{col 62}{space 2} .1625211{col 73}{space 1}    1.92{col 82}{space 3}0.057{col 90}{space 4}-.0097137{col 103}{space 3} .6348571
{txt}{space 45}14  {c |}{col 50}{res}{space 2} .1564549{col 62}{space 2} .1099584{col 73}{space 1}    1.42{col 82}{space 3}0.158{col 90}{space 4}-.0615968{col 103}{space 3} .3745066
{txt}{space 45}15  {c |}{col 50}{res}{space 2} .2315708{col 62}{space 2} .1541193{col 73}{space 1}    1.50{col 82}{space 3}0.136{col 90}{space 4}-.0740536{col 103}{space 3} .5371952
{txt}{space 45}16  {c |}{col 50}{res}{space 2} .2036262{col 62}{space 2} .2878053{col 73}{space 1}    0.71{col 82}{space 3}0.481{col 90}{space 4}-.3671026{col 103}{space 3} .7743549
{txt}{space 45}17  {c |}{col 50}{res}{space 2} .0448662{col 62}{space 2} .1876938{col 73}{space 1}    0.24{col 82}{space 3}0.812{col 90}{space 4}-.3273377{col 103}{space 3} .4170701
{txt}{space 45}18  {c |}{col 50}{res}{space 2} .3070149{col 62}{space 2} .1691494{col 73}{space 1}    1.82{col 82}{space 3}0.072{col 90}{space 4}-.0284148{col 103}{space 3} .6424445
{txt}{space 45}19  {c |}{col 50}{res}{space 2} .1787304{col 62}{space 2} .1143507{col 73}{space 1}    1.56{col 82}{space 3}0.121{col 90}{space 4}-.0480313{col 103}{space 3} .4054921
{txt}{space 45}20  {c |}{col 50}{res}{space 2} .0581008{col 62}{space 2}  .120137{col 73}{space 1}    0.48{col 82}{space 3}0.630{col 90}{space 4}-.1801353{col 103}{space 3} .2963369
{txt}{space 45}21  {c |}{col 50}{res}{space 2} .2102934{col 62}{space 2} .1096684{col 73}{space 1}    1.92{col 82}{space 3}0.058{col 90}{space 4}-.0071832{col 103}{space 3}   .42777
{txt}{space 45}22  {c |}{col 50}{res}{space 2}  .146704{col 62}{space 2}  .173681{col 73}{space 1}    0.84{col 82}{space 3}0.400{col 90}{space 4} -.197712{col 103}{space 3}   .49112
{txt}{space 45}23  {c |}{col 50}{res}{space 2}-.1049804{col 62}{space 2} .0877232{col 73}{space 1}   -1.20{col 82}{space 3}0.234{col 90}{space 4}-.2789387{col 103}{space 3}  .068978
{txt}{space 45}24  {c |}{col 50}{res}{space 2} .2472369{col 62}{space 2} .1222333{col 73}{space 1}    2.02{col 82}{space 3}0.046{col 90}{space 4} .0048437{col 103}{space 3} .4896302
{txt}{space 45}25  {c |}{col 50}{res}{space 2}  .188364{col 62}{space 2} .1485732{col 73}{space 1}    1.27{col 82}{space 3}0.208{col 90}{space 4}-.1062622{col 103}{space 3} .4829903
{txt}{space 45}26  {c |}{col 50}{res}{space 2}  .051121{col 62}{space 2} .1314143{col 73}{space 1}    0.39{col 82}{space 3}0.698{col 90}{space 4}-.2094786{col 103}{space 3} .3117205
{txt}{space 45}27  {c |}{col 50}{res}{space 2} .3566714{col 62}{space 2} .1969728{col 73}{space 1}    1.81{col 82}{space 3}0.073{col 90}{space 4} -.033933{col 103}{space 3} .7472758
{txt}{space 45}28  {c |}{col 50}{res}{space 2}-.0505634{col 62}{space 2} .1114801{col 73}{space 1}   -0.45{col 82}{space 3}0.651{col 90}{space 4}-.2716327{col 103}{space 3} .1705059
{txt}{space 45}29  {c |}{col 50}{res}{space 2} .0789215{col 62}{space 2} .1874125{col 73}{space 1}    0.42{col 82}{space 3}0.675{col 90}{space 4}-.2927245{col 103}{space 3} .4505675
{txt}{space 45}30  {c |}{col 50}{res}{space 2} .1606611{col 62}{space 2} .1732403{col 73}{space 1}    0.93{col 82}{space 3}0.356{col 90}{space 4}-.1828809{col 103}{space 3} .5042032
{txt}{space 45}31  {c |}{col 50}{res}{space 2}-.0204618{col 62}{space 2} .1789511{col 73}{space 1}   -0.11{col 82}{space 3}0.909{col 90}{space 4}-.3753285{col 103}{space 3} .3344048
{txt}{space 45}32  {c |}{col 50}{res}{space 2} .2045148{col 62}{space 2} .1423029{col 73}{space 1}    1.44{col 82}{space 3}0.154{col 90}{space 4}-.0776772{col 103}{space 3} .4867067
{txt}{space 45}33  {c |}{col 50}{res}{space 2}  .118591{col 62}{space 2} .0895287{col 73}{space 1}    1.32{col 82}{space 3}0.188{col 90}{space 4}-.0589478{col 103}{space 3} .2961299
{txt}{space 45}34  {c |}{col 50}{res}{space 2}-.1482565{col 62}{space 2} .2272184{col 73}{space 1}   -0.65{col 82}{space 3}0.516{col 90}{space 4}-.5988391{col 103}{space 3} .3023261
{txt}{space 45}35  {c |}{col 50}{res}{space 2} .1391519{col 62}{space 2} .1023796{col 73}{space 1}    1.36{col 82}{space 3}0.177{col 90}{space 4}-.0638707{col 103}{space 3} .3421746
{txt}{space 45}36  {c |}{col 50}{res}{space 2} .2118097{col 62}{space 2} .1350507{col 73}{space 1}    1.57{col 82}{space 3}0.120{col 90}{space 4}-.0560009{col 103}{space 3} .4796203
{txt}{space 45}37  {c |}{col 50}{res}{space 2} .1960934{col 62}{space 2}   .11494{col 73}{space 1}    1.71{col 82}{space 3}0.091{col 90}{space 4} -.031837{col 103}{space 3} .4240238
{txt}{space 45}38  {c |}{col 50}{res}{space 2} .3091081{col 62}{space 2} .1961057{col 73}{space 1}    1.58{col 82}{space 3}0.118{col 90}{space 4}-.0797768{col 103}{space 3}  .697993
{txt}{space 45}39  {c |}{col 50}{res}{space 2} .2153445{col 62}{space 2} .1177258{col 73}{space 1}    1.83{col 82}{space 3}0.070{col 90}{space 4}-.0181103{col 103}{space 3} .4487992
{txt}{space 45}40  {c |}{col 50}{res}{space 2} .0422852{col 62}{space 2} .0782473{col 73}{space 1}    0.54{col 82}{space 3}0.590{col 90}{space 4}-.1128822{col 103}{space 3} .1974525
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{txt}{space 45}42  {c |}{col 50}{res}{space 2} .2196908{col 62}{space 2} .1605742{col 73}{space 1}    1.37{col 82}{space 3}0.174{col 90}{space 4}-.0987338{col 103}{space 3} .5381154
{txt}{space 45}43  {c |}{col 50}{res}{space 2}  .005958{col 62}{space 2} .0738741{col 73}{space 1}    0.08{col 82}{space 3}0.936{col 90}{space 4} -.140537{col 103}{space 3} .1524531
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{txt}{space 45}45  {c |}{col 50}{res}{space 2} .2193136{col 62}{space 2} .1204122{col 73}{space 1}    1.82{col 82}{space 3}0.071{col 90}{space 4}-.0194682{col 103}{space 3} .4580955
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{txt}{space 45}47  {c |}{col 50}{res}{space 2} .1533221{col 62}{space 2} .0923288{col 73}{space 1}    1.66{col 82}{space 3}0.100{col 90}{space 4}-.0297693{col 103}{space 3} .3364135
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{txt}{space 45}49  {c |}{col 50}{res}{space 2} .3317607{col 62}{space 2} .2043139{col 73}{space 1}    1.62{col 82}{space 3}0.107{col 90}{space 4}-.0734014{col 103}{space 3} .7369228
{txt}{space 45}50  {c |}{col 50}{res}{space 2}   .34343{col 62}{space 2} .1845623{col 73}{space 1}    1.86{col 82}{space 3}0.066{col 90}{space 4}-.0225641{col 103}{space 3}  .709424
{txt}{space 45}51  {c |}{col 50}{res}{space 2} .3367137{col 62}{space 2} .2317516{col 73}{space 1}    1.45{col 82}{space 3}0.149{col 90}{space 4}-.1228584{col 103}{space 3} .7962859
{txt}{space 45}52  {c |}{col 50}{res}{space 2} .2356811{col 62}{space 2}  .231323{col 73}{space 1}    1.02{col 82}{space 3}0.311{col 90}{space 4}-.2230412{col 103}{space 3} .6944033
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{txt}{space 45}54  {c |}{col 50}{res}{space 2} .2900711{col 62}{space 2} .1841997{col 73}{space 1}    1.57{col 82}{space 3}0.118{col 90}{space 4}-.0752039{col 103}{space 3}  .655346
{txt}{space 45}55  {c |}{col 50}{res}{space 2} .4152907{col 62}{space 2} .2352938{col 73}{space 1}    1.76{col 82}{space 3}0.081{col 90}{space 4}-.0513057{col 103}{space 3}  .881887
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{txt}{space 45}58  {c |}{col 50}{res}{space 2} .1979467{col 62}{space 2} .1743902{col 73}{space 1}    1.14{col 82}{space 3}0.259{col 90}{space 4}-.1478756{col 103}{space 3} .5437689
{txt}{space 45}59  {c |}{col 50}{res}{space 2} .1958284{col 62}{space 2} .2090721{col 73}{space 1}    0.94{col 82}{space 3}0.351{col 90}{space 4}-.2187694{col 103}{space 3} .6104262
{txt}{space 45}60  {c |}{col 50}{res}{space 2} .1438021{col 62}{space 2} .1035455{col 73}{space 1}    1.39{col 82}{space 3}0.168{col 90}{space 4}-.0615325{col 103}{space 3} .3491367
{txt}{space 45}61  {c |}{col 50}{res}{space 2} .1356466{col 62}{space 2} .1104842{col 73}{space 1}    1.23{col 82}{space 3}0.222{col 90}{space 4}-.0834478{col 103}{space 3} .3547409
{txt}{space 45}62  {c |}{col 50}{res}{space 2}  .319178{col 62}{space 2} .2067186{col 73}{space 1}    1.54{col 82}{space 3}0.126{col 90}{space 4}-.0907527{col 103}{space 3} .7291086
{txt}{space 45}63  {c |}{col 50}{res}{space 2} .3886986{col 62}{space 2} .2011519{col 73}{space 1}    1.93{col 82}{space 3}0.056{col 90}{space 4}-.0101931{col 103}{space 3} .7875903
{txt}{space 45}64  {c |}{col 50}{res}{space 2}  .399441{col 62}{space 2}  .210988{col 73}{space 1}    1.89{col 82}{space 3}0.061{col 90}{space 4}-.0189561{col 103}{space 3} .8178381
{txt}{space 45}65  {c |}{col 50}{res}{space 2} .2116965{col 62}{space 2} .1213154{col 73}{space 1}    1.75{col 82}{space 3}0.084{col 90}{space 4}-.0288765{col 103}{space 3} .4522696
{txt}{space 45}66  {c |}{col 50}{res}{space 2} .1906643{col 62}{space 2} .2236739{col 73}{space 1}    0.85{col 82}{space 3}0.396{col 90}{space 4}-.2528896{col 103}{space 3} .6342181
{txt}{space 45}67  {c |}{col 50}{res}{space 2} .2223817{col 62}{space 2} .1367944{col 73}{space 1}    1.63{col 82}{space 3}0.107{col 90}{space 4}-.0488867{col 103}{space 3} .4936501
{txt}{space 45}68  {c |}{col 50}{res}{space 2} .2798301{col 62}{space 2} .1525853{col 73}{space 1}    1.83{col 82}{space 3}0.070{col 90}{space 4}-.0227524{col 103}{space 3} .5824126
{txt}{space 45}69  {c |}{col 50}{res}{space 2} .1405676{col 62}{space 2} .1226848{col 73}{space 1}    1.15{col 82}{space 3}0.255{col 90}{space 4} -.102721{col 103}{space 3} .3838563
{txt}{space 45}70  {c |}{col 50}{res}{space 2} .3490297{col 62}{space 2} .2107443{col 73}{space 1}    1.66{col 82}{space 3}0.101{col 90}{space 4}-.0688841{col 103}{space 3} .7669435
{txt}{space 45}71  {c |}{col 50}{res}{space 2}-.1056926{col 62}{space 2} .1816268{col 73}{space 1}   -0.58{col 82}{space 3}0.562{col 90}{space 4}-.4658652{col 103}{space 3} .2544801
{txt}{space 45}72  {c |}{col 50}{res}{space 2} .1998043{col 62}{space 2} .1183712{col 73}{space 1}    1.69{col 82}{space 3}0.094{col 90}{space 4}-.0349302{col 103}{space 3} .4345388
{txt}{space 45}73  {c |}{col 50}{res}{space 2} .4232625{col 62}{space 2} .1922105{col 73}{space 1}    2.20{col 82}{space 3}0.030{col 90}{space 4} .0421019{col 103}{space 3} .8044232
{txt}{space 45}74  {c |}{col 50}{res}{space 2} .1509798{col 62}{space 2} .1023571{col 73}{space 1}    1.48{col 82}{space 3}0.143{col 90}{space 4}-.0519982{col 103}{space 3} .3539578
{txt}{space 45}75  {c |}{col 50}{res}{space 2} .0692116{col 62}{space 2} .1504222{col 73}{space 1}    0.46{col 82}{space 3}0.646{col 90}{space 4}-.2290812{col 103}{space 3} .3675044
{txt}{space 45}76  {c |}{col 50}{res}{space 2} .2933042{col 62}{space 2} .1726225{col 73}{space 1}    1.70{col 82}{space 3}0.092{col 90}{space 4}-.0490126{col 103}{space 3}  .635621
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{txt}{space 45}78  {c |}{col 50}{res}{space 2}  .268771{col 62}{space 2} .1092554{col 73}{space 1}    2.46{col 82}{space 3}0.016{col 90}{space 4} .0521135{col 103}{space 3} .4854286
{txt}{space 45}79  {c |}{col 50}{res}{space 2}-.0171477{col 62}{space 2} .0253791{col 73}{space 1}   -0.68{col 82}{space 3}0.501{col 90}{space 4}-.0674755{col 103}{space 3} .0331801
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{txt}{space 45}81  {c |}{col 50}{res}{space 2} .1546914{col 62}{space 2} .2384522{col 73}{space 1}    0.65{col 82}{space 3}0.518{col 90}{space 4}-.3181683{col 103}{space 3} .6275511
{txt}{space 45}82  {c |}{col 50}{res}{space 2} .2345835{col 62}{space 2} .2040921{col 73}{space 1}    1.15{col 82}{space 3}0.253{col 90}{space 4}-.1701388{col 103}{space 3} .6393059
{txt}{space 45}83  {c |}{col 50}{res}{space 2} .3426125{col 62}{space 2} .1690587{col 73}{space 1}    2.03{col 82}{space 3}0.045{col 90}{space 4} .0073628{col 103}{space 3} .6778622
{txt}{space 45}84  {c |}{col 50}{res}{space 2}  .285569{col 62}{space 2} .2072614{col 73}{space 1}    1.38{col 82}{space 3}0.171{col 90}{space 4}-.1254381{col 103}{space 3} .6965761
{txt}{space 45}85  {c |}{col 50}{res}{space 2} .3042401{col 62}{space 2} .1611318{col 73}{space 1}    1.89{col 82}{space 3}0.062{col 90}{space 4}-.0152904{col 103}{space 3} .6237705
{txt}{space 45}86  {c |}{col 50}{res}{space 2}  .327308{col 62}{space 2} .2402581{col 73}{space 1}    1.36{col 82}{space 3}0.176{col 90}{space 4}-.1491329{col 103}{space 3} .8037489
{txt}{space 45}87  {c |}{col 50}{res}{space 2} .3828455{col 62}{space 2}  .240279{col 73}{space 1}    1.59{col 82}{space 3}0.114{col 90}{space 4}-.0936367{col 103}{space 3} .8593277
{txt}{space 45}88  {c |}{col 50}{res}{space 2} .1692685{col 62}{space 2} .1689581{col 73}{space 1}    1.00{col 82}{space 3}0.319{col 90}{space 4}-.1657817{col 103}{space 3} .5043188
{txt}{space 45}89  {c |}{col 50}{res}{space 2} .2280671{col 62}{space 2} .1642594{col 73}{space 1}    1.39{col 82}{space 3}0.168{col 90}{space 4}-.0976655{col 103}{space 3} .5537997
{txt}{space 45}90  {c |}{col 50}{res}{space 2} .0208483{col 62}{space 2} .0838704{col 73}{space 1}    0.25{col 82}{space 3}0.804{col 90}{space 4}-.1454699{col 103}{space 3} .1871666
{txt}{space 45}91  {c |}{col 50}{res}{space 2} .1413463{col 62}{space 2} .1180712{col 73}{space 1}    1.20{col 82}{space 3}0.234{col 90}{space 4}-.0927934{col 103}{space 3}  .375486
{txt}{space 45}92  {c |}{col 50}{res}{space 2} .0818692{col 62}{space 2} .0596795{col 73}{space 1}    1.37{col 82}{space 3}0.173{col 90}{space 4}-.0364775{col 103}{space 3}  .200216
{txt}{space 45}93  {c |}{col 50}{res}{space 2} .3531603{col 62}{space 2} .1730011{col 73}{space 1}    2.04{col 82}{space 3}0.044{col 90}{space 4} .0100927{col 103}{space 3} .6962279
{txt}{space 45}94  {c |}{col 50}{res}{space 2} .4489066{col 62}{space 2} .2122187{col 73}{space 1}    2.12{col 82}{space 3}0.037{col 90}{space 4} .0280689{col 103}{space 3} .8697442
{txt}{space 45}95  {c |}{col 50}{res}{space 2} .1686254{col 62}{space 2}  .208145{col 73}{space 1}    0.81{col 82}{space 3}0.420{col 90}{space 4}-.2441339{col 103}{space 3} .5813847
{txt}{space 45}96  {c |}{col 50}{res}{space 2} .2935213{col 62}{space 2}  .188265{col 73}{space 1}    1.56{col 82}{space 3}0.122{col 90}{space 4}-.0798153{col 103}{space 3} .6668579
{txt}{space 45}97  {c |}{col 50}{res}{space 2} .3303288{col 62}{space 2} .1539356{col 73}{space 1}    2.15{col 82}{space 3}0.034{col 90}{space 4} .0250687{col 103}{space 3} .6355888
{txt}{space 45}98  {c |}{col 50}{res}{space 2} .4414333{col 62}{space 2} .2216153{col 73}{space 1}    1.99{col 82}{space 3}0.049{col 90}{space 4} .0019619{col 103}{space 3} .8809047
{txt}{space 45}99  {c |}{col 50}{res}{space 2} .0442372{col 62}{space 2} .0560515{col 73}{space 1}    0.79{col 82}{space 3}0.432{col 90}{space 4}-.0669151{col 103}{space 3} .1553894
{txt}{space 44}100  {c |}{col 50}{res}{space 2} .2082151{col 62}{space 2} .2102827{col 73}{space 1}    0.99{col 82}{space 3}0.324{col 90}{space 4}-.2087833{col 103}{space 3} .6252136
{txt}{space 44}101  {c |}{col 50}{res}{space 2} .3667419{col 62}{space 2} .1666323{col 73}{space 1}    2.20{col 82}{space 3}0.030{col 90}{space 4} .0363038{col 103}{space 3} .6971799
{txt}{space 44}102  {c |}{col 50}{res}{space 2} .2770513{col 62}{space 2} .2136655{col 73}{space 1}    1.30{col 82}{space 3}0.198{col 90}{space 4}-.1466553{col 103}{space 3}  .700758
{txt}{space 44}103  {c |}{col 50}{res}{space 2}  .079555{col 62}{space 2}  .117205{col 73}{space 1}    0.68{col 82}{space 3}0.499{col 90}{space 4}-.1528668{col 103}{space 3} .3119768
{txt}{space 44}104  {c |}{col 50}{res}{space 2}-.1599948{col 62}{space 2} .0602993{col 73}{space 1}   -2.65{col 82}{space 3}0.009{col 90}{space 4}-.2795706{col 103}{space 3}-.0404191
{txt}{space 44}105  {c |}{col 50}{res}{space 2} .2271054{col 62}{space 2} .1994805{col 73}{space 1}    1.14{col 82}{space 3}0.258{col 90}{space 4}-.1684719{col 103}{space 3} .6226827
{txt}{space 48} {c |}
{space 44}year {c |}
{space 43}2011  {c |}{col 50}{res}{space 2}-.0023778{col 62}{space 2} .0037712{col 73}{space 1}   -0.63{col 82}{space 3}0.530{col 90}{space 4}-.0098563{col 103}{space 3} .0051007
{txt}{space 43}2012  {c |}{col 50}{res}{space 2} .0045383{col 62}{space 2} .0045279{col 73}{space 1}    1.00{col 82}{space 3}0.319{col 90}{space 4}-.0044406{col 103}{space 3} .0135173
{txt}{space 43}2013  {c |}{col 50}{res}{space 2} .0026149{col 62}{space 2} .0056398{col 73}{space 1}    0.46{col 82}{space 3}0.644{col 90}{space 4} -.008569{col 103}{space 3} .0137988
{txt}{space 43}2014  {c |}{col 50}{res}{space 2}-.0024395{col 62}{space 2} .0066076{col 73}{space 1}   -0.37{col 82}{space 3}0.713{col 90}{space 4}-.0155426{col 103}{space 3} .0106637
{txt}{space 43}2015  {c |}{col 50}{res}{space 2}-.0102991{col 62}{space 2} .0080024{col 73}{space 1}   -1.29{col 82}{space 3}0.201{col 90}{space 4}-.0261681{col 103}{space 3} .0055699
{txt}{space 43}2016  {c |}{col 50}{res}{space 2} -.013314{col 62}{space 2} .0079792{col 73}{space 1}   -1.67{col 82}{space 3}0.098{col 90}{space 4}-.0291369{col 103}{space 3}  .002509
{txt}{space 43}2017  {c |}{col 50}{res}{space 2}-.0030192{col 62}{space 2} .0118204{col 73}{space 1}   -0.26{col 82}{space 3}0.799{col 90}{space 4}-.0264594{col 103}{space 3}  .020421
{txt}{space 43}2018  {c |}{col 50}{res}{space 2}-.0294569{col 62}{space 2} .0107816{col 73}{space 1}   -2.73{col 82}{space 3}0.007{col 90}{space 4}-.0508371{col 103}{space 3}-.0080766
{txt}{space 43}2019  {c |}{col 50}{res}{space 2}-.0686042{col 62}{space 2} .0121605{col 73}{space 1}   -5.64{col 82}{space 3}0.000{col 90}{space 4} -.092719{col 103}{space 3}-.0444895
{txt}{space 48} {c |}
{space 26}ln_ratio_mnmsup_mnmsub {c |}{col 50}{res}{space 2}        0{col 62}{txt}  (omitted)
{space 40}1.gender {c |}{col 50}{res}{space 2}        0{col 62}{txt}  (omitted)
{space 48} {c |}
{space 17}gender#c.ln_ratio_mnmsup_mnmsub {c |}
{space 46}1  {c |}{col 50}{res}{space 2} .0076218{col 62}{space 2} .0196178{col 73}{space 1}    0.39{col 82}{space 3}0.698{col 90}{space 4} -.031281{col 103}{space 3} .0465246
{txt}{space 48} {c |}
{space 31}gender#supervisor {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2} .0003686{col 62}{space 2} .0109099{col 73}{space 1}    0.03{col 82}{space 3}0.973{col 90}{space 4}-.0212662{col 103}{space 3} .0220034
{txt}{space 48} {c |}
{space 6}gender#supervisor#c.ln_ratio_mnmsup_mnmsub {c |}
{space 44}1 1  {c |}{col 50}{res}{space 2}-.0038293{col 62}{space 2} .0234075{col 73}{space 1}   -0.16{col 82}{space 3}0.870{col 90}{space 4}-.0502472{col 103}{space 3} .0425887
{txt}{space 48} {c |}
{space 43}_cons {c |}{col 50}{res}{space 2}  .041386{col 62}{space 2} .5058031{col 73}{space 1}    0.08{col 82}{space 3}0.935{col 90}{space 4}-.9616406{col 103}{space 3} 1.044413
{txt}{hline 49}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *
. estat ic

{txt}Akaike's information criterion and Bayesian information criterion

{hline 13}{c TT}{hline 63}
       Model {c |}          N   ll(null)  ll(model)      df        AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16} 2,507,103{col 28} -1943049{col 39} -1891092{col 50}    28{col 58}  3782241{col 69}  3782597
{txt}{hline 13}{c BT}{hline 63}
{p 0 6 0 77}Note: BIC uses N = number of observations. See {helpb bic_note:{bind:[R] IC note}}.{p_end}

{com}. *
. 
. ** BY NON-SUPERVISORS RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0471792{col 26}{space 2} .0345551{col 37}{space 1}    1.37{col 46}{space 3}0.175{col 54}{space 4}-.0213448{col 67}{space 3} .1157032
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0189138{col 26}{space 2} .0198446{col 37}{space 1}    0.95{col 46}{space 3}0.343{col 54}{space 4}-.0204388{col 67}{space 3} .0582664
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0487378{col 26}{space 2} .0185456{col 37}{space 1}    2.63{col 46}{space 3}0.010{col 54}{space 4} .0119611{col 67}{space 3} .0855145
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub - 1.minority_het#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0298239{col 26}{space 2} .0167396{col 37}{space 1}    1.78{col 46}{space 3}0.078{col 54}{space 4}-.0033714{col 67}{space 3} .0630192
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. *
. *
. *
. *
. *
. 
. 
. ** BY SUPERVISOR RESPONDENT: BETWEEN-IDENTITY "IN" GROUP VERSUS "OUT" GROUP STATUS DIFFERENTIAL BETWEEN MINORITY/NON-MINORITY RESPONDENTS **
. 
. lincom c.ln_ratio_mnmsup_mnmsub+ 1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}ln_ratio_mnmsup_mnmsub + 1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}  .060059{col 26}{space 2}  .041802{col 37}{space 1}    1.44{col 46}{space 3}0.154{col 54}{space 4} -.022836{col 67}{space 3}  .142954
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#c.ln_ratio_mnmsup_mnmsub + 1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0676854{col 26}{space 2} .0202958{col 37}{space 1}    3.33{col 46}{space 3}0.001{col 54}{space 4}  .027438{col 67}{space 3} .1079327
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0642712{col 26}{space 2} .0210191{col 37}{space 1}    3.06{col 46}{space 3}0.003{col 54}{space 4} .0225895{col 67}{space 3} .1059528
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- 1.minority_het#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#c.ln_ratio_mnmsup_mnmsub - 1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub + 2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0034142{col 26}{space 2} .0252754{col 37}{space 1}   -0.14{col 46}{space 3}0.893{col 54}{space 4}-.0535362{col 67}{space 3} .0467078
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. *
. *
. *
. 
. 
. * SUPERVISOR - NON-SUPERVISORY DIFFERENCE AMONG MINORITY RESPONDENT DIFFERENCES [MINORITY MEN RESPONDENTS FOLLOWED BY MINORITY WOMEN RESPONDENTS] -- DO NOT PLOT IN GRAPHS [ONLY FOR TEXT]!
. 
. lincom  1.minority_het#c.ln_ratio_mnmsup_mnmsub +  1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (1.minority_het#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}1.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0487715{col 26}{space 2} .0166907{col 37}{space 1}    2.92{col 46}{space 3}0.004{col 54}{space 4} .0156733{col 67}{space 3} .0818697
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *
. lincom  2.minority_het#c.ln_ratio_mnmsup_mnmsub +  2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub - (2.minority_het#c.ln_ratio_mnmsup_mnmsub)

{p 0 7}{space 1}{text:( 1)}{space 1} {res}2.minority_het#1.supervisor#c.ln_ratio_mnmsup_mnmsub = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}lndiversit~j{col 14}{c |} Coefficient{col 26}  Std. err.{col 38}      t{col 46}   P>|t|{col 54}     [95% con{col 67}f. interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0155334{col 26}{space 2} .0249986{col 37}{space 1}    0.62{col 46}{space 3}0.536{col 54}{space 4}-.0340397{col 67}{space 3} .0651065
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. clear
{txt}
{com}. 
. *** FIGURE I1: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS I1 & I2 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 1] **
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figurei1.xlsx", sheet("Sheet1") firstrow
{res}{text}(5 vars, 7 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(circle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE I1" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(By Respondent Single Social Identity Group)" "[Sensitivity of AD Estimates When Controlling for Social Identity Group Spillover Effects]", size(small)) ylabel(-0.1(.1)0.3, labsize (small) angle(horizon)) xtitle("AD Estimates [Differentials by Responsdent Single Social Identity Group]" "(Models 1&2)", size(small)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE I2: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS I3 & I4 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 2]  **
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figurei2.xlsx", sheet("Sheet1") firstrow
{res}{text}(10 vars, 12 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(circle_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==4, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==5, msymbol(square) mcolor(navy))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 6 "Race/Ethnicity") pos(6)) title("FIGURE I2"  "Relationship Between Authority Differentials and D&I Employee Evaluations" `"(By Respondent Intersectional Social Identity Group)"' "[Sensitivity of AD Estimates When Controlling for Social Identity Group Spillover Effects]", size(small)) ylabel(-0.1(.1)0.3, labsize (small) angle(horizon)) xtitle("Gender AD Effects: by Respondent Intersectionality Group   Race/Ethnicity AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}.   
. clear
{txt}
{com}. 
. *** FIGURE I3: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS I5-I8 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 3] **
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figurei3.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE I3" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(Non-Supervisory Respondents: Single and Intersectional Social Identity Groups)" "[Sensitivity of AD Estimates When Controlling for Social Identity Group Spillover Effects]", size(small)) ylabel(-0.05(.05)0.2, labsize (small) angle(horizon)) xtitle("AD Effects: by Respondent Single Identity Group     AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *** FIGURE I4: PLOT ELASTICITY MARGINAL EFFECTS FOR MODELS I5-I8 USING LINCOMS ABOVE FOR EACH MODEL: PATTERN AFTER COMPARABLE SET OF MANUSCRIPT GRAPHICS/FIGURES [FIGURE 4]  **
. import excel "C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\figurei4.xlsx", sheet("Sheet1") firstrow
{res}{text}(14 vars, 18 obs)

{com}. destring, replace
{txt}row already numeric; no {res}replace
{txt}group already numeric; no {res}replace
{txt}estimates already numeric; no {res}replace
{txt}low95 already numeric; no {res}replace
{txt}high95 already numeric; no {res}replace
{txt}F already numeric; no {res}replace
{txt}G already numeric; no {res}replace
{txt}H already numeric; no {res}replace
{txt}I already numeric; no {res}replace
{txt}J already numeric; no {res}replace
{txt}K already numeric; no {res}replace
{txt}L already numeric; no {res}replace
{txt}M already numeric; no {res}replace
{txt}N already numeric; no {res}replace
{txt}
{com}. 
. set scheme sj, permanently
{txt}({cmd:set scheme} preference recorded)

{com}. graph set window fontface "Century Schoolbook"
{txt}
{com}. 
. twoway (rcap low95 high95 row, vert) (scatter estimates row if group ==1, msymbol(square) mcolor(orange))(scatter estimates row if group ==2, msymbol(square_hollow) mcolor(orange)) (scatter estimates row if group ==3, msymbol(square) mcolor(navy))(scatter estimates row if group ==4, msymbol(square_hollow) mcolor(navy))(scatter estimates row if group ==5, msymbol(square) mcolor(orange))(scatter estimates row if group ==6, msymbol(circle_hollow) mcolor(orange))(scatter estimates row if group ==7, msymbol(diamond_hollow) mcolor(orange))(scatter estimates row if group ==8, msymbol(triangle_hollow) mcolor(orange))(scatter estimates row if group ==9, msymbol(square) mcolor(navy))(scatter estimates row if group ==10, msymbol(circle_hollow) mcolor(navy))(scatter estimates row if group ==11, msymbol(diamond_hollow) mcolor(navy))(scatter estimates row if group ==12, msymbol(triangle_hollow) mcolor(navy)), legend(row(1) order(2 "Gender" 4 "Race/Ethnicity") pos(6)) title("FIGURE I4" "Relationship Between Authority Differentials and D&I Employee Evaluations" "(Supervisor Respondents: Single and Intersectional Social Identity Groups)" "[Sensitivity of AD Estimates When Controlling for Social Identity Group Spillover Effects]", size(small)) ylabel(-0.1(.1)0.3, labsize (small) angle(horizon)) xtitle("AD Effects: by Respondent Single Identity Group     AD Effects: by Respondent Intersectionality Group", size(vsmall)) xlabel("", noticks) yline(0, lpattern(dash) lcolor(gs8)) aspect(.5)
{res}{txt}
{com}.    
. 
. ******************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************
. 
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\jungy\Dropbox\DISCRIMINATION PROJECT\Organizational Diversity\Statistics\Krause & Park.Authority Differentials.APPENDIX I RESULTS.08-07-2024.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 7 Aug 2024, 22:25:49
{txt}{.-}
{smcl}
{txt}{sf}{ul off}